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train · 6.25k rows

Conference stringclasses 6 values	Year int64 1.99k 2.03k	Title stringlengths 8 187	DOI stringlengths 16 32	Abstract stringlengths 128 7.15k ⌀	Accessible bool 2 classes	Early bool 2 classes	AuthorNames-Deduped listlengths 1 29	Award listlengths 0 2	Resources listlengths 0 5	ResourceLinks listlengths 0 10
EuroVis	2,021	Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth	10.1111/cgf.14332	We present a state‐of‐the‐art report on visualization in astrophysics. We survey representative papers from both astrophysics and visualization and provide a taxonomy of existing approaches based on data analysis tasks. The approaches are classified based on five categories: data wrangling, data exploration, feature id...	false	false	[ "Fangfei Lan", "Michael Young", "Lauren Anderson", "Anders Ynnerman", "Alexander Bock 0002", "Michelle A. Borkin", "Angus G. Forbes", "Juna A. Kollmeier", "Bei Wang 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2106.00152v1", "icon": "paper" } ]
EuroVis	2,021	Visualizing Carotid Blood Flow Simulations for Stroke Prevention	10.1111/cgf.14319	In this work, we investigate how concepts from medical flow visualization can be applied to enhance stroke prevention diagnostics. Our focus lies on carotid stenoses, i.e., local narrowings of the major brain‐supplying arteries, which are a frequent cause of stroke. Carotid surgery can reduce the stroke risk associated...	false	false	[ "Pepe Eulzer", "Monique Meuschke", "Carsten M. Klingner", "Kai Lawonn" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2104.02654v1", "icon": "paper" } ]
EuroVis	2,021	What are Table Cartograms Good for Anyway? An Algebraic Analysis	10.1111/cgf.14289	Unfamiliar or esoteric visual forms arise in many areas of visualization. While such forms can be intriguing, it can be unclear how to make effective use of them without long periods of practice or costly user studies. In this work we analyze the table cartogram—a graphic which visualizes tabular data by bringing the a...	false	false	[ "Andrew M. McNutt" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2104.04042v1", "icon": "paper" } ]
CHI	2,021	[email protected]: Fostering Visual Exploration of Personal Data on Smartphones Leveraging Speech and Touch Interaction	10.1145/3411764.3445421	Most mobile health apps employ data visualization to help people view their health and activity data, but these apps provide limited support for visual data exploration. Furthermore, despite its huge potential benefits, mobile visualization research in the personal data context is sparse. This work aims to empower peop...	false	false	[ "Young-Ho Kim", "Bongshin Lee", "Arjun Srinivasan", "Eun Kyoung Choe" ]	[]	[]	[]
CHI	2,021	A Review on Strategies for Data Collection, Reflection, and Communication in Eating Disorder Apps	10.1145/3411764.3445670	Eating disorders (EDs) constitute a mental illness with the highest mortality. Today, mobile health apps provide promising means to ED patients for managing their condition. Apps enable users to monitor their eating habits, thoughts, and feelings, and offer analytic insights for behavior change. However, not only have ...	false	false	[ "Anjali Devakumar", "Jay Modh", "Bahador Saket", "Eric P. S. Baumer", "Munmun De Choudhury" ]	[]	[]	[]
CHI	2,021	A Visual Analytics Approach to Facilitate the Proctoring of Online Exams	10.1145/3411764.3445294	Online exams have become widely used to evaluate students’ performance in mastering knowledge in recent years, especially during the pandemic of COVID-19. However, it is challenging to conduct proctoring for online exams due to the lack of face-to-face interaction. Also, prior research has shown that online exams are m...	false	false	[ "Haotian Li 0001", "Min Xu", "Yong Wang 0021", "Huan Wei", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.07990v1", "icon": "paper" } ]
CHI	2,021	CakeVR: A Social Virtual Reality (VR) Tool for Co-designing Cakes	10.1145/3411764.3445503	Cake customization services allow clients to collaboratively personalize cakes with pastry chefs. However, remote (e.g., email) and in-person co-design sessions are prone to miscommunication, due to natural restrictions in visualizing cake size, decoration, and celebration context. This paper presents the design, imple...	false	false	[ "Yanni Mei", "Jie Li 0064", "Huib de Ridder", "Pablo César" ]	[]	[]	[]
CHI	2,021	Can Anthropographics Promote Prosociality?A Review and Large-Sample Study	10.1145/3411764.3445637	Visualizations designed to make readers compassionate with the persons whose data is represented have been called anthropographics and are commonly employed by practitioners. Empirical studies have recently examined whether anthropographics indeed promote empathy, compassion, or the likelihood of prosocial behavior, bu...	false	false	[ "Luiz Augusto de Macêdo Morais", "Yvonne Jansen", "Nazareno Andrade", "Pierre Dragicevic" ]	[]	[]	[]
CHI	2,021	Collecting and Characterizing Natural Language Utterances for Specifying Data Visualizations	10.1145/3411764.3445400	Natural language interfaces (NLIs) for data visualization are becoming increasingly popular both in academic research and in commercial software. Yet, there is a lack of empirical understanding of how people specify visualizations through natural language. We conducted an online study (N = 102), showing participants a ...	false	false	[ "Arjun Srinivasan", "Nikhila Nyapathy", "Bongshin Lee", "Steven Mark Drucker", "John T. Stasko" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2110.00680v1", "icon": "paper" } ]
CHI	2,021	Communicating with Motion: A Design Space for Animated Visual Narratives in Data Videos	10.1145/3411764.3445337	Data videos are a genre of narrative visualization that communicates stories by combining data visualization and motion graphics. While data videos are increasingly gaining popularity, few systematic reviews or structured analyses exist for their design. In this work, we introduce a design space for animated visual nar...	false	false	[ "Yang Shi 0007", "Xingyu Lan", "Jingwen Li", "Zhaorui Li", "Nan Cao 0001" ]	[]	[]	[]
CHI	2,021	Comparison of Different Types of Augmented Reality Visualizations for Instructions	10.1145/3411764.3445724	Augmented Reality (AR) is increasingly being used for providing guidance and supporting troubleshooting in industrial settings. While the general application of AR has been shown to provide clear benefits regarding physical tasks, it is important to understand how different visualization types influence user’s performa...	false	false	[ "Florian Jasche", "Sven Hoffmann", "Thomas Ludwig 0005", "Volker Wulf" ]	[]	[]	[]
CHI	2,021	ConceptScope: Organizing and Visualizing Knowledge in Documents based on Domain Ontology	10.1145/3411764.3445396	Current text visualization techniques typically provide overviews of document content and structure using intrinsic properties such as term frequencies, co-occurrences, and sentence structures. Such visualizations lack conceptual overviews incorporating domain-relevant knowledge, needed when examining documents such as...	false	false	[ "Xiaoyu Zhang", "Senthil K. Chandrasegaran", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2003.05108v2", "icon": "paper" } ]
CHI	2,021	Data Animator: Authoring Expressive Animated Data Graphics	10.1145/3411764.3445747	Animation helps viewers follow transitions in data graphics. When authoring animations that incorporate data, designers must carefully coordinate the behaviors of visual objects such as entering, exiting, merging and splitting, and specify the temporal rhythms of transition through staging and staggering. We present Da...	false	false	[ "John R. Thompson 0002", "Zhicheng Liu 0001", "John T. Stasko" ]	[]	[]	[]
CHI	2,021	Data Prophecy: Exploring the Effects of Belief Elicitation in Visual Analytics	10.1145/3411764.3445798	Interactive visualizations are widely used in exploratory data analysis, but existing systems provide limited support for confirmatory analysis. We introduce PredictMe, a tool for belief-driven visual analysis, enabling users to draw and test their beliefs against data, as an alternative to data-driven exploration. Pre...	false	false	[ "Ratanond Koonchanok", "Parul Baser", "Abhinav Sikharam", "Nirmal Kumar Raveendranath", "Khairi Reda" ]	[]	[]	[]
CHI	2,021	Design and Analysis of Intelligent Text Entry Systems with Function Structure Models and Envelope Analysis	10.1145/3411764.3445566	Designing intelligent interactive text entry systems often relies on factors that are difficult to estimate or assess using traditional HCI design and evaluation methods. We introduce a complementary approach by adapting function structure models from engineering design. We extend their use by extracting controllable a...	false	false	[ "Per Ola Kristensson", "Thomas Müllners" ]	[]	[]	[]
CHI	2,021	Designing CAST: A Computer-Assisted Shadowing Trainer for Self-Regulated Foreign Language Listening Practice	10.1145/3411764.3445190	Shadowing, i.e., listening to recorded native speech and simultaneously vocalizing the words, is a popular language-learning technique that is known to improve listening skills. However, despite strong evidence for its efficacy as a listening exercise, existing shadowing systems do not adequately support listening-focu...	false	false	[ "Mohi Reza", "Dongwook Yoon" ]	[]	[]	[]
CHI	2,021	Digital Transformations of Classrooms in Virtual Reality	10.1145/3411764.3445596	With rapid developments in consumer-level head-mounted displays and computer graphics, immersive VR has the potential to take online and remote learning closer to real-world settings. However, the effects of such digital transformations on learners, particularly for VR, have not been evaluated in depth. This work inves...	false	false	[ "Hong Gao 0008", "Efe Bozkir", "Lisa Hasenbein", "Jens-Uwe Hahn", "Richard Göllner", "Enkelejda Kasneci" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.09576v2", "icon": "paper" } ]
CHI	2,021	Does Interaction Improve Bayesian Reasoning with Visualization?	10.1145/3411764.3445176	Interaction enables users to navigate large amounts of data effectively, supports cognitive processing, and increases data representation methods. However, there have been few attempts to empirically demonstrate whether adding interaction to a static visualization improves its function beyond popular beliefs. In this p...	false	false	[ "Abigail Mosca", "Alvitta Ottley", "Remco Chang" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2103.01701v2", "icon": "paper" } ]
CHI	2,021	Effect of Information Presentation on Fairness Perceptions of Machine Learning Predictors	10.1145/3411764.3445365	The uptake of artificial intelligence-based applications raises concerns about the fairness and transparency of AI behaviour. Consequently, the Computer Science community calls for the involvement of the general public in the design and evaluation of AI systems. Assessing the fairness of individual predictors is an ess...	false	false	[ "Niels van Berkel", "Jorge Gonçalves 0001", "Daniel Russo 0002", "Simo Hosio", "Mikael B. Skov" ]	[]	[]	[]
CHI	2,021	Effects of Semantic Segmentation Visualization on Trust, Situation Awareness, and Cognitive Load in Highly Automated Vehicles	10.1145/3411764.3445351	Autonomous vehicles could improve mobility, safety, and inclusion in traffic. While this technology seems within reach, its successful introduction depends on the intended user’s acceptance. A substantial factor for this acceptance is trust in the autonomous vehicle’s capabilities. Visualizing internal information proc...	false	false	[ "Mark Colley", "Benjamin Eder", "Jan Ole Rixen", "Enrico Rukzio" ]	[]	[]	[]
CHI	2,021	Falx: Synthesis-Powered Visualization Authoring	10.1145/3411764.3445249	Modern visualization tools aim to allow data analysts to easily create exploratory visualizations. When the input data layout conforms to the visualization design, users can easily specify visualizations by mapping data columns to visual channels of the design. However, when there is a mismatch between data layout and ...	false	false	[ "Chenglong Wang", "Yu Feng 0001", "Rastislav Bodík", "Isil Dillig", "Alvin Cheung", "Amy J. Ko" ]	[ "BP" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2102.01024v1", "icon": "paper" } ]
CHI	2,021	FashionQ: An AI-Driven Creativity Support Tool for Facilitating Ideation in Fashion Design	10.1145/3411764.3445093	Recent research on creativity support tools (CST) adopts artificial intelligence (AI) that leverages big data and computational capabilities to facilitate creative work. Our work aims to articulate the role of AI in supporting creativity with a case study of an AI-based CST tool in fashion design based on theoretical g...	false	false	[ "Youngseung Jeon", "Seungwan Jin", "Patrick C. Shih", "Kyungsik Han" ]	[]	[]	[]
CHI	2,021	Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop	10.1145/3411764.3445775	AutoML systems can speed up routine data science work and make machine learning available to those without expertise in statistics and computer science. These systems have gained traction in enterprise settings where pools of skilled data workers are limited. In this study, we conduct interviews with 29 individuals fro...	false	false	[ "Anamaria Crisan", "Brittany Fiore-Gartland" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.04296v1", "icon": "paper" } ]
CHI	2,021	From Detectables to Inspectables: Understanding Qualitative Analysis of Audiovisual Data	10.1145/3411764.3445458	Audiovisual recordings of user studies and interviews provide important data in qualitative HCI research. Even when a textual transcription is available, researchers frequently turn to these recordings due to their rich information content. However, the temporal, unstructured nature of audiovisual recordings makes them...	false	false	[ "Krishna Subramanian 0002", "Johannes Maas", "Jan O. Borchers", "James D. Hollan" ]	[ "HM" ]	[]	[]
CHI	2,021	GestureMap: Supporting Visual Analytics and Quantitative Analysis of Motion Elicitation Data by Learning 2D Embeddings	10.1145/3411764.3445765	This paper presents GestureMap, a visual analytics tool for gesture elicitation which directly visualises the space of gestures. Concretely, a Variational Autoencoder embeds gestures recorded as 3D skeletons on an interactive 2D map. GestureMap further integrates three computational capabilities to connect exploration ...	false	false	[ "Hai Dang", "Daniel Buschek" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2103.00912v1", "icon": "paper" } ]
CHI	2,021	Grand Challenges in Immersive Analytics	10.1145/3411764.3446866	Immersive Analytics is a quickly evolving field that unites several areas such as visualisation, immersive environments, and human-computer interaction to support human data analysis with emerging technologies. This research has thrived over the past years with multiple workshops, seminars, and a growing body of public...	false	false	[ "Barrett Ens", "Benjamin Bach", "Maxime Cordeil", "Ulrich Engelke", "Marcos Serrano", "Wesley Willett", "Arnaud Prouzeau", "Christoph Anthes", "Wolfgang Büschel", "Cody Dunne", "Tim Dwyer", "Jens Grubert", "Jason H. Haga", "Nurit Kirshenbaum", "Dylan Kobayashi", "Tica Lin", "Monsurat...	[]	[]	[]
CHI	2,021	Haptic and Visual Comprehension of a 2D Graph Layout Through Physicalisation	10.1145/3411764.3445704	Data physicalisations afford people the ability to directly interact with data using their hands, potentially achieving a more comprehensive understanding of a dataset. Due to their complex nature, the representation of graphs and networks could benefit from physicalisation, bringing the dataset from the digital world ...	false	false	[ "Adam Drogemuller", "Andrew Cunningham", "James A. Walsh", "James Baumeister", "Ross T. Smith", "Bruce H. Thomas" ]	[]	[]	[]
CHI	2,021	IGScript: An Interaction Grammar for Scientific Data Presentation	10.1145/3411764.3445535	Most of the existing scientific visualizations toward interpretive grammar aim to enhance customizability in either the computation stage or the rendering stage or both, while few approaches focus on the data presentation stage. Besides, most of these approaches leverage the existing components from the general-purpose...	false	false	[ "Richen Liu", "Min Gao", "Shunlong Ye", "Jiang Zhang 0002" ]	[]	[]	[]
CHI	2,021	Integrated Visualization Editing via Parameterized Declarative Templates	10.1145/3411764.3445356	Interfaces for creating visualizations typically embrace one of several common forms. Textual specification enables fine-grained control, shelf building facilitates rapid exploration, while chart choosing promotes immediacy and simplicity. Ideally these approaches could be unified to integrate the user- and usage-depen...	false	false	[ "Andrew M. McNutt", "Ravi Chugh" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.07902v2", "icon": "paper" } ]
CHI	2,021	Interpreting the Effect of Embellishment on Chart Visualizations	10.1145/3411764.3445739	Infographics range from minimalism that aims to convey the raw data to elaborately decorated, or embellished, graphics that aim to engage readers by telling a story. Several studies have shown evidence to negative, but also positive, effects on embellishments. We conducted a set of experiments to gauge more precisely h...	false	false	[ "Tiffany Andry", "Christophe Hurter", "François Lambotte", "Pierre Fastrez", "Alexandru C. Telea" ]	[]	[]	[]
CHI	2,021	Investigating the Impact of Real-World Environments on the Perception of 2D Visualizations in Augmented Reality	10.1145/3411764.3445330	In this work we report on two comprehensive user studies investigating the perception of Augmented Reality (AR) visualizations influenced by real-world backgrounds. Since AR is an emerging technology, it is important to also consider productive use cases, which is why we chose an exemplary and challenging industry 4.0 ...	false	false	[ "Marc Satkowski", "Raimund Dachselt" ]	[]	[]	[]
CHI	2,021	It's a Wrap: Toroidal Wrapping of Network Visualisations Supports Cluster Understanding Tasks	10.1145/3411764.3445439	We explore network visualisation on a two-dimensional torus topology that continuously wraps when the viewport is panned. That is, links may be “wrapped” across the boundary, allowing additional spreading of node positions to reduce visual clutter. Recent work has investigated such pannable wrapped visualisations, find...	false	false	[ "Kun-Ting Chen", "Tim Dwyer", "Benjamin Bach", "Kim Marriott" ]	[]	[]	[]
CHI	2,021	LaserFactory: A Laser Cutter-based Electromechanical Assembly and Fabrication Platform to Make Functional Devices & Robots	10.1145/3411764.3445692	LaserFactory is an integrated fabrication process that augments a commercially available fabrication machine to support the manufacture of fully functioning devices without human intervention. In addition to creating 2D and 3D mechanical structures, LaserFactory creates conductive circuit traces with arbitrary geometri...	false	false	[ "Martin Nisser", "Christina Chen Liao", "Yuchen Chai", "Aradhana Adhikari", "Steve Hodges 0001", "Stefanie Müller 0001" ]	[]	[]	[]
CHI	2,021	Little Road Driving HUD: Heads-Up Display Complexity Influences Drivers' Perceptions of Automated Vehicles	10.1145/3411764.3445575	Modern vehicles are using AI and increasingly sophisticated sensor suites to improve Advanced Driving Assistance Systems (ADAS) and support automated driving capabilities. Heads-Up-Displays (HUDs) provide an opportunity to visually inform drivers about vehicle perception and interpretation of the driving environment. O...	false	false	[ "Rebecca Currano", "So Yeon Park", "Dylan James Moore", "Kent Lyons", "David Sirkin" ]	[]	[]	[]
CHI	2,021	Locomotion Vault: the Extra Mile in Analyzing VR Locomotion Techniques	10.1145/3411764.3445319	Numerous techniques have been proposed for locomotion in virtual reality (VR). Several taxonomies consider a large number of attributes (e.g., hardware, accessibility) to characterize these techniques. However, finding the appropriate locomotion technique (LT) and identifying gaps for future designs in the high-dimensi...	false	false	[ "Massimiliano Di Luca", "Hasti Seifi", "Simon Egan", "Mar González-Franco" ]	[]	[]	[]
CHI	2,021	Mapping the Landscape of COVID-19 Crisis Visualizations	10.1145/3411764.3445381	In response to COVID-19, a vast number of visualizations have been created to communicate information to the public. Information exposure in a public health crisis can impact people’s attitudes towards and responses to the crisis and risks, and ultimately the trajectory of a pandemic. As such, there is a need for work ...	false	false	[ "Yixuan Zhang 0001", "Yifan Sun 0002", "Lace M. K. Padilla", "Sumit Barua", "Enrico Bertini", "Andrea G. Parker" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.04743v1", "icon": "paper" } ]
CHI	2,021	MARVIS: Combining Mobile Devices and Augmented Reality for Visual Data Analysis	10.1145/3411764.3445593	We present Marvis, a conceptual framework that combines mobile devices and head-mounted Augmented Reality (AR) for visual data analysis. We propose novel concepts and techniques addressing visualization-specific challenges. By showing additional 2D and 3D information around and above displays, we extend their limited s...	false	false	[ "Ricardo Langner", "Marc Satkowski", "Wolfgang Büschel", "Raimund Dachselt" ]	[]	[]	[]
CHI	2,021	MIRIA: A Mixed Reality Toolkit for the In-Situ Visualization and Analysis of Spatio-Temporal Interaction Data	10.1145/3411764.3445651	In this paper, we present MIRIA, a Mixed Reality Interaction Analysis toolkit designed to support the in-situ visual analysis of user interaction in mixed reality and multi-display environments. So far, there are few options to effectively explore and analyze interaction patterns in such novel computing systems. With M...	false	false	[ "Wolfgang Büschel", "Anke Lehmann", "Raimund Dachselt" ]	[]	[]	[]
CHI	2,021	Modeling and Leveraging Analytic Focus During Exploratory Visual Analysis	10.1145/3411764.3445674	Visual analytics systems enable highly interactive exploratory data analysis. Across a range of fields, these technologies have been successfully employed to help users learn from complex data. However, these same exploratory visualization techniques make it easy for users to discover spurious findings. This paper prop...	false	false	[ "Zhilan Zhou", "Ximing Wen", "Yue Wang 0035", "David Gotz" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.08856v1", "icon": "paper" } ]
CHI	2,021	mTSeer: Interactive Visual Exploration of Models on Multivariate Time-series Forecast	10.1145/3411764.3445083	Time-series forecasting contributes crucial information to industrial and institutional decision-making with multivariate time-series input. Although various models have been developed to facilitate the forecasting process, they make inconsistent forecasts. Thus, it is critical to select the model appropriately. The ex...	false	false	[ "Ke Xu", "Jun Yuan", "Yifang Wang 0001", "Cláudio T. Silva", "Enrico Bertini" ]	[]	[]	[]
CHI	2,021	NBSearch: Semantic Search and Visual Exploration of Computational Notebooks	10.1145/3411764.3445048	Code search is an important and frequent activity for developers using computational notebooks (e.g., Jupyter). The flexibility of notebooks brings challenges for effective code search, where classic search interfaces for traditional software code may be limited. In this paper, we propose, NBSearch, a novel system that...	false	false	[ "Xingjun Li", "Yuanxin Wang", "Hong Wang", "Yang Wang", "Jian Zhao 0010" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2102.01275v1", "icon": "paper" } ]
CHI	2,021	PriView- Exploring Visualisations to Support Users' Privacy Awareness	10.1145/3411764.3445067	We present PriView, a concept that allows privacy-invasive devices in the users’ vicinity to be visualised. PriView is motivated by an ever-increasing number of sensors in our environments tracking potentially sensitive data (e.g., audio and video). At the same time, users are oftentimes unaware of this, which violates...	false	false	[ "Sarah Prange", "Ahmed Shams", "Robin Piening", "Yomna Abdelrahman", "Florian Alt" ]	[]	[]	[]
CHI	2,021	Quantitative Data Visualisation on Virtual Globes	10.1145/3411764.3445152	Geographic data visualisation on virtual globes is intuitive and widespread, but has not been thoroughly investigated. We explore two main design factors for quantitative data visualisation on virtual globes: i) commonly used primitives (2D bar, 3D bar, circle) and ii) the orientation of these primitives (tangential, n...	false	false	[ "Kadek Ananta Satriadi", "Barrett Ens", "Tobias Czauderna", "Maxime Cordeil", "Bernhard Jenny" ]	[]	[]	[]
CHI	2,021	RCEA-360VR: Real-time, Continuous Emotion Annotation in 360° VR Videos for Collecting Precise Viewport-dependent Ground Truth Labels	10.1145/3411764.3445487	Precise emotion ground truth labels for 360° virtual reality (VR) video watching are essential for fine-grained predictions under varying viewing behavior. However, current annotation techniques either rely on post-stimulus discrete self-reports, or real-time, continuous emotion annotations (RCEA) but only for desktop/...	false	false	[ "Tong Xue", "Abdallah El Ali", "Tianyi Zhang", "Gangyi Ding", "Pablo César" ]	[]	[]	[]
CHI	2,021	Reconfiguration Strategies with Composite Data Physicalizations	10.1145/3411764.3445746	Composite data physicalizations allow for the physical reconfiguration of data points, creating new opportunities for interaction and engagement. However, there is a lack of understanding of people’s strategies and behaviors when directly manipulating physical data objects. In this paper, we systematically characterize...	false	false	[ "Kim Sauvé", "David Verweij", "Jason Alexander", "Steven Houben" ]	[]	[]	[]
CHI	2,021	reVISit: Looking Under the Hood of Interactive Visualization Studies	10.1145/3411764.3445382	Quantifying user performance with metrics such as time and accuracy does not show the whole picture when researchers evaluate complex, interactive visualization tools. In such systems, performance is often influenced by different analysis strategies that statistical analysis methods cannot account for. To remedy this l...	false	false	[ "Carolina Nobre", "Dylan Wootton", "Zach Cutler", "Lane Harrison", "Hanspeter Pfister", "Alexander Lex" ]	[]	[]	[]
CHI	2,021	Soloist: Generating Mixed-Initiative Tutorials from Existing Guitar Instructional Videos Through Audio Processing	10.1145/3411764.3445162	Learning musical instruments using online instructional videos has become increasingly prevalent. However, pre-recorded videos lack the instantaneous feedback and personal tailoring that human tutors provide. In addition, existing video navigations are not optimized for instrument learning, making the learning experien...	false	false	[ "Bryan Wang", "Mengyu Yang", "Tovi Grossman" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.08846v1", "icon": "paper" } ]
CHI	2,021	STREAM: Exploring the Combination of Spatially-Aware Tablets with Augmented Reality Head-Mounted Displays for Immersive Analytics	10.1145/3411764.3445298	Recent research in the area of immersive analytics demonstrated the utility of head-mounted augmented reality devices for visual data analysis. However, it can be challenging to use the by default supported mid-air gestures to interact with visualizations in augmented reality (e.g. due to limited precision). Touch-base...	false	false	[ "Sebastian Hubenschmid", "Johannes Zagermann", "Simon Butscher", "Harald Reiterer" ]	[]	[]	[]
CHI	2,021	Tele-Immersive Improv: Effects of Immersive Visualisations on Rehearsing and Performing Theatre Online	10.1145/3411764.3445310	Performers acutely need but lack tools to remotely rehearse and create live theatre, particularly due to global restrictions on social interactions during the Covid-19 pandemic. No studies, however, have heretofore examined how remote video-collaboration affects performance. This paper presents the findings of a field ...	false	false	[ "Boyd Branch", "Christos Efstratiou", "Piotr Mirowski", "Kory W. Mathewson", "Paul Allain" ]	[]	[]	[]
CHI	2,021	The Public Life of Data: Investigating Reactions to Visualizations on Reddit	10.1145/3411764.3445720	This research investigates how people engage with data visualizations when commenting on the social platform Reddit. There has been considerable research on collaborative sensemaking with visualizations and the personal relation of people with data. Yet, little is known about how public audiences without specific exper...	false	false	[ "Tobias Kauer", "Marian Dörk", "Arran L. Ridley", "Benjamin Bach" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2103.08525v2", "icon": "paper" } ]
CHI	2,021	Towards an Understanding of Situated AR Visualization for Basketball Free-Throw Training	10.1145/3411764.3445649	We present an observational study to compare co-located and situated real-time visualizations in basketball free-throw training. Our goal is to understand the advantages and concerns of applying immersive visualization to real-world skill-based sports training and to provide insights for designing AR sports training sy...	false	false	[ "Tica Lin", "Rishi Singh", "Yalong Yang 0001", "Carolina Nobre", "Johanna Beyer", "Maurice A. Smith", "Hanspeter Pfister" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2104.04118v2", "icon": "paper" } ]
CHI	2,021	Understanding Data Accessibility for People with Intellectual and Developmental Disabilities	10.1145/3411764.3445743	Using visualization requires people to read abstract visual imagery, estimate statistics, and retain information. However, people with Intellectual and Developmental Disabilities (IDD) often process information differently, which may complicate connecting abstract visual information to real-world quantities. This popul...	false	false	[ "Keke Wu", "Emma Petersen", "Tahmina Ahmad", "David Burlinson", "Shea Tanis", "Danielle Albers Szafir" ]	[ "BP" ]	[]	[]
CHI	2,021	Understanding Narrative Linearity for Telling Expressive Time-Oriented Stories	10.1145/3411764.3445344	Creating expressive narrative visualization often requires choosing a well-planned narrative order that invites the audience in. The narrative can either follow the linear order of story events (chronology), or deviate from linearity (anachronies). While evidence exists that anachronies in novels and films can enhance ...	false	false	[ "Xingyu Lan", "Xinyue Xu", "Nan Cao" ]	[]	[]	[]
CHI	2,021	Understanding Trigger-Action Programs Through Novel Visualizations of Program Differences	10.1145/3411764.3445567	Trigger-action programming (if-this-then-that rules) empowers non-technical users to automate services and smart devices. As a user’s set of trigger-action programs evolves, the user must reason about behavior differences between similar programs, such as between an original program and several modification candidates,...	false	false	[ "Valerie Zhao", "Lefan Zhang", "Bo Wang", "Michael L. Littman", "Shan Lu 0001", "Blase Ur" ]	[ "HM" ]	[]	[]
CHI	2,021	Viral Visualizations: How Coronavirus Skeptics Use Orthodox Data Practices to Promote Unorthodox Science Online	10.1145/3411764.3445211	Controversial understandings of the coronavirus pandemic have turned data visualizations into a battleground. Defying public health officials, coronavirus skeptics on US social media spent much of 2020 creating data visualizations showing that the government’s pandemic response was excessive and that the crisis was ove...	false	false	[ "Crystal Lee", "Tanya Yang", "Gabrielle D. Inchoco", "Graham M. Jones", "Arvind Satyanarayan" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.07993v1", "icon": "paper" } ]
CHI	2,021	Vis Ex Machina: An Analysis of Trust in Human versus Algorithmically Generated Visualization Recommendations	10.1145/3411764.3445195	More visualization systems are simplifying the data analysis process by automatically suggesting relevant visualizations. However, little work has been done to understand if users trust these automated recommendations. In this paper, we present the results of a crowd-sourced study exploring preferences and perceived qu...	false	false	[ "Rachael Zehrung", "Astha Singhal", "Michael Correll", "Leilani Battle" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2101.04251v2", "icon": "paper" } ]
CHI	2,021	Visualizing Examples of Deep Neural Networks at Scale	10.1145/3411764.3445654	Many programmers want to use deep learning due to its superior accuracy in many challenging domains. Yet our formative study with ten programmers indicated that, when constructing their own deep neural networks (DNNs), they often had a difficult time choosing appropriate model structures and hyperparameter values. This...	false	false	[ "Litao Yan", "Elena L. Glassman", "Tianyi Zhang 0001" ]	[ "HM" ]	[]	[]
CHI	2,021	What Players Want: Information Needs of Players on Post-Game Visualizations	10.1145/3411764.3445174	With the rise of competitive online gaming and esports, players’ ability to review, reflect upon, and improve their in-game performance has become important. Post-play visualizations are key for such improvements. Despite the increased interest in visualizations of gameplay, research specifically informing the design o...	false	false	[ "Günter Wallner", "Marnix van Wijland", "Regina Bernhaupt", "Simone Kriglstein" ]	[]	[]	[]
VAST	2,020	A Visual Analytics Approach for Ecosystem Dynamics based on Empirical Dynamic Modeling	10.1109/TVCG.2020.3028956	An important approach for scientific inquiry across many disciplines involves using observational time series data to understand the relationships between key variables to gain mechanistic insights into the underlying rules that govern the given system. In real systems, such as those found in ecology, the relationships...	false	false	[ "Hiroaki Natsukawa", "Ethan R. Deyle", "Gerald M. Pao", "Koji Koyamada", "George Sugihara" ]	[]	[ "V" ]	[ { "name": "Fast Forward", "url": "https://youtu.be/6n0nG2FcZxA", "icon": "video" } ]
VAST	2,020	A Visual Analytics Approach for Exploratory Causal Analysis: Exploration, Validation, and Applications	10.1109/TVCG.2020.3028957	Using causal relations to guide decision making has become an essential analytical task across various domains, from marketing and medicine to education and social science. While powerful statistical models have been developed for inferring causal relations from data, domain practitioners still lack effective visual in...	false	false	[ "Xiao Xie", "Fan Du", "Yingcai Wu" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02458v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/hpNhFtKaSq8", "icon": "video" } ]
VAST	2,020	A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems’ Worldviews	10.1109/VAST50239.2020.00008	Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot’s abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi-robot system that uses the shared-world coordination paradigm autonom...	false	false	[ "Sandra Bae", "Federico Rossi 0001", "Joshua Vander Hook", "Scott Davidoff", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.01921v1", "icon": "paper" } ]
VAST	2,020	A Visual Analytics Framework for Contrastive Network Analysis	10.1109/VAST50239.2020.00010	A common network analysis task is comparison of two networks to identify unique characteristics in one network with respect to the other. For example, when comparing protein interaction networks derived from normal and cancer tissues, one essential task is to discover protein-protein interactions unique to cancer tissu...	false	false	[ "Takanori Fujiwara", "Jian Zhao 0010", "Francine Chen 0001", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.00151v2", "icon": "paper" } ]
VAST	2,020	A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes	10.1109/TVCG.2020.3028888	Many statistical learning models hold an assumption that the training data and the future unlabeled data are drawn from the same distribution. However, this assumption is difficult to fulfill in real-world scenarios and creates barriers in reusing existing labels from similar application domains. Transfer Learning is i...	false	false	[ "Yuxin Ma", "Arlen Fan", "Jingrui He", "Arun Reddy Nelakurthi", "Ross Maciejewski" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.06876v1", "icon": "paper" } ]
VAST	2,020	A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction	10.1109/TVCG.2020.3028889	Data-driven problem solving in many real-world applications involves analysis of time-dependent multivariate data, for which dimensionality reduction (DR) methods are often used to uncover the intrinsic structure and features of the data. However, DR is usually applied to a subset of data that is either single-time-poi...	false	false	[ "Takanori Fujiwara", "Shilpika", "Naohisa Sakamoto", "Jorji Nonaka", "Keiji Yamamoto", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.01645v3", "icon": "paper" } ]
VAST	2,020	An Examination of Grouping and Spatial Organization Tasks for High-Dimensional Data Exploration	10.1109/TVCG.2020.3028890	How do analysts think about grouping and spatial operations? This overarching research question incorporates a number of points for investigation, including understanding how analysts begin to explore a dataset, the types of grouping/spatial structures created and the operations performed on them, the relationship betw...	false	false	[ "John E. Wenskovitch", "Chris North 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.09233v1", "icon": "paper" } ]
VAST	2,020	Argus: Interactive a priori Power Analysis	10.1109/TVCG.2020.3028894	A key challenge HCl researchers face when designing a controlled experiment is choosing the appropriate number of participants, or sample size. A priori power analysis examines the relationships among multiple parameters, including the complexity associated with human participants, e.g., order and fatigue effects, to c...	false	false	[ "Xiaoyi Wang", "Alexander Eiselmayer", "Wendy E. Mackay", "Kasper Hornbæk", "Chat Wacharamanotham" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.07564v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/gWoDjnGejGQ", "icon": "video" } ]
VAST	2,020	Attention Flows: Analyzing and Comparing Attention Mechanisms in Language Models	10.1109/TVCG.2020.3028976	Advances in language modeling have led to the development of deep attention-based models that are performant across a wide variety of natural language processing (NLP) problems. These language models are typified by a pre-training process on large unlabeled text corpora and subsequently fine-tuned for specific tasks. A...	false	false	[ "Joseph F. DeRose", "Jiayao Wang", "Matthew Berger" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.07053v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/rz3BpEVpS7E", "icon": "video" } ]
VAST	2,020	Auditing the Sensitivity of Graph-based Ranking with Visual Analytics	10.1109/TVCG.2020.3028958	Graph mining plays a pivotal role across a number of disciplines, and a variety of algorithms have been developed to answer who/what type questions. For example, what items shall we recommend to a given user on an e-commerce platform? The answers to such questions are typically returned in the form of a ranked list, an...	false	false	[ "Tiankai Xie", "Yuxin Ma", "Hanghang Tong", "My T. Thai", "Ross Maciejewski" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.07227v1", "icon": "paper" } ]
VAST	2,020	Boba: Authoring and Visualizing Multiverse Analyses	10.1109/TVCG.2020.3028985	Multiverse analysis is an approach to data analysis in which all “reasonable” analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustness and transparency. However, specifying a multiverse is demanding because analysts must manage myriad variants from a cross-product of anal...	false	false	[ "Yang Liu 0136", "Alex Kale", "Tim Althoff", "Jeffrey Heer" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.05551v2", "icon": "paper" } ]
VAST	2,020	CAVA: A Visual Analytics System for Exploratory Columnar Data Augmentation Using Knowledge Graphs	10.1109/TVCG.2020.3030443	Most visual analytics systems assume that all foraging for data happens before the analytics process; once analysis begins, the set of data attributes considered is fixed. Such separation of data construction from analysis precludes iteration that can enable foraging informed by the needs that arise in-situ during the ...	false	false	[ "Dylan Cashman", "Shenyu Xu", "Subhajit Das 0002", "Florian Heimerl", "Cong Liu", "Shah Rukh Humayoun", "Michael Gleicher", "Alex Endert", "Remco Chang" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02865v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/mOidkJ_0_3U", "icon": "video" } ]
VAST	2,020	CcNav: Understanding Compiler Optimizations in Binary Code	10.1109/TVCG.2020.3030357	Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming a...	false	false	[ "Sabin Devkota", "Pascal Aschwanden", "Adam Kunen", "Matthew P. LeGendre", "Katherine E. Isaacs" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.00956v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/Y3yjiyfNf48", "icon": "video" } ]
VAST	2,020	CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization	10.1109/TVCG.2020.3030418	Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying deep learning. We present CNN Explainer, an interactive visualization tool designed...	false	false	[ "Zijie J. Wang", "Robert Turko", "Omar Shaikh", "Haekyu Park", "Nilaksh Das", "Fred Hohman", "Minsuk Kahng", "Polo Chau" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2004.15004v3", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/SlEvmkS4Rs4", "icon": "video" } ]
VAST	2,020	CNNPruner: Pruning Convolutional Neural Networks with Visual Analytics	10.1109/TVCG.2020.3030461	Convolutional neural networks (CNNs) have demonstrated extraordinarily good performance in many computer vision tasks. The increasing size of CNN models, however, prevents them from being widely deployed to devices with limited computational resources, e.g., mobile/embedded devices. The emerging topic of model pruning ...	false	false	[ "Guan Li", "Junpeng Wang", "Han-Wei Shen", "Kaixin Chen 0004", "Guihua Shan", "Zhonghua Lu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.09940v1", "icon": "paper" } ]
VAST	2,020	Co-Bridges: Pair-wise Visual Connection and Comparison for Multi-item Data Streams	10.1109/TVCG.2020.3030411	In various domains, there are abundant streams or sequences of multi-item data of various kinds, e.g. streams of news and social media texts, sequences of genes and sports events, etc. Comparison is an important and general task in data analysis. For comparing data streams involving multiple items (e.g., words in texts...	false	false	[ "Siming Chen 0001", "Natalia V. Andrienko", "Gennady L. Andrienko", "Jie Li 0006", "Xiaoru Yuan" ]	[]	[]	[]
VAST	2,020	Competing Models: Inferring Exploration Patterns and Information Relevance via Bayesian Model Selection	10.1109/TVCG.2020.3030430	Analyzing interaction data provides an opportunity to learn about users, uncover their underlying goals, and create intelligent visualization systems. The first step for intelligent response in visualizations is to enable computers to infer user goals and strategies through observing their interactions with a system. R...	false	false	[ "Shayan Monadjemi", "Roman Garnett", "Alvitta Ottley" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.06042v2", "icon": "paper" } ]
VAST	2,020	ConceptExplorer: Visual Analysis of Concept Drifts in Multi-source Time-series Data	10.1109/VAST50239.2020.00006	Time-series data is widely studied in various scenarios, like weather forecast, stock market, customer behavior analysis. To comprehensively learn about the dynamic environments, it is necessary to comprehend features from multiple data sources. This paper proposes a novel visual analysis approach for detecting and ana...	false	false	[ "Xumeng Wang", "Wei Chen 0001", "Jiazhi Xia", "Zexian Chen", "Dongshi Xu", "Xiangyang Wu", "Mingliang Xu", "Tobias Schreck" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.15272v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/KqB3Gy1eHvQ", "icon": "video" } ]
VAST	2,020	DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models	10.1109/TVCG.2020.3030342	With machine learning models being increasingly applied to various decision-making scenarios, people have spent growing efforts to make machine learning models more transparent and explainable. Among various explanation techniques, counterfactual explanations have the advantages of being human-friendly and actionable-a...	false	false	[ "Furui Cheng", "Yao Ming", "Huamin Qu" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.08353v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/wVrJ5youWNU", "icon": "video" } ]
VAST	2,020	Diagnosing Concept Drift with Visual Analytics	10.1109/VAST50239.2020.00007	Concept drift is a phenomenon in which the distribution of a data stream changes over time in unforeseen ways, causing prediction models built on historical data to become inaccurate. While a variety of automated methods have been developed to identify when concept drift occurs, there is limited support for analysts wh...	false	false	[ "Weikai Yang", "Zhen Li 0044", "Mengchen Liu", "Yafeng Lu", "Kelei Cao", "Ross Maciejewski", "Shixia Liu" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.14372v3", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/449t1pfeKq0", "icon": "video" } ]
VAST	2,020	Evaluation of Sampling Methods for Scatterplots	10.1109/TVCG.2020.3030432	Given a scatterplot with tens of thousands of points or even more, a natural question is which sampling method should be used to create a small but “good” scatterplot for a better abstraction. We present the results of a user study that investigates the influence of different sampling strategies on multi-class scatterp...	false	false	[ "Jun Yuan 0003", "Shouxing Xiang", "Jiazhi Xia", "Lingyun Yu 0001", "Shixia Liu" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.14666v4", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/gPtAZsJKO5I", "icon": "video" } ]
VAST	2,020	Explainable Matrix - Visualization for Global and Local Interpretability of Random Forest Classification Ensembles	10.1109/TVCG.2020.3030354	Over the past decades, classification models have proven to be essential machine learning tools given their potential and applicability in various domains. In these years, the north of the majority of the researchers had been to improve quantitative metrics, notwithstanding the lack of information about models' decisio...	false	false	[ "Mário Popolin Neto", "Fernando Vieira Paulovich" ]	[]	[ "V" ]	[ { "name": "Fast Forward", "url": "https://youtu.be/qlthySP_mwA", "icon": "video" } ]
VAST	2,020	Githru: Visual Analytics for Understanding Software Development History Through Git Metadata Analysis	10.1109/TVCG.2020.3030414	Git metadata contains rich information for developers to understand the overall context of a large software development project. Thus it can help new developers, managers, and testers understand the history of development without needing to dig into a large pile of unfamiliar source code. However, the current tools for...	false	false	[ "Youngtaek Kim", "Jaeyoung Kim", "Hyeon Jeon", "Young-Ho Kim", "Hyunjoo Song", "Bo Hyoung Kim", "Jinwook Seo" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.03115v2", "icon": "paper" } ]
VAST	2,020	HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networks	10.1109/TVCG.2020.3030380	To mitigate the pain of manually tuning hyperparameters of deep neural networks, automated machine learning (AutoML) methods have been developed to search for an optimal set of hyperparameters in large combinatorial search spaces. However, the search results of AutoML methods significantly depend on initial configurati...	false	false	[ "Heungseok Park", "Yoonsoo Nam", "Jihoon Kim", "Jaegul Choo" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02078v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/3nD6kXCL2xI", "icon": "video" } ]
VAST	2,020	HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models	10.1109/TVCG.2020.3030449	In this paper, we present a visual analytics tool for enabling hypothesis-based evaluation of machine learning (ML) models. We describe a novel ML-testing framework that combines the traditional statistical hypothesis testing (commonly used in empirical research) with logical reasoning about the conclusions of multiple...	false	false	[ "Qianwen Wang", "William Alexander", "Jack Pegg", "Huamin Qu", "Min Chen 0001" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2002.05271v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/rf-amrd2Goc", "icon": "video" } ]
VAST	2,020	iConViz: Interactive Visual Exploration of the Default Contagion Risk of Networked-Guarantee Loans	10.1109/VAST50239.2020.00013	Groups of enterprises can serve as guarantees for one another and form complex networks when obtaining loans from commercial banks. During economic slowdowns, corporate default may spread like a virus and lead to large-scale defaults or even systemic financial crises. To help financial regulatory authorities and banks ...	false	false	[ "Zhibin Niu", "Runlin Li", "Junqi Wu", "Dawei Cheng", "Jiawan Zhang" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2006.09542v3", "icon": "paper" } ]
VAST	2,020	II-20: Intelligent and pragmatic analytic categorization of image collections	10.1109/TVCG.2020.3030383	In this paper, we introduce 11–20 (Image Insight 2020), a multimedia analytics approach for analytic categorization of image collections. Advanced visualizations for image collections exist, but they need tight integration with a machine model to support the task of analytic categorization. Directly employing computer ...	false	false	[ "Jan Zahálka", "Marcel Worring", "Jarke J. van Wijk" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2005.02149v3", "icon": "paper" } ]
VAST	2,020	In Search of Patient Zero: Visual Analytics of Pathogen Transmission Pathways in Hospitals	10.1109/TVCG.2020.3030437	Pathogen outbreaks (i.e., outbreaks of bacteria and viruses) in hospitals can cause high mortality rates and increase costs for hospitals significantly. An outbreak is generally noticed when the number of infected patients rises above an endemic level or the usual prevalence of a pathogen in a defined population. Recon...	false	false	[ "Tom Baumgartl", "Markus Petzold", "Marcel Wunderlich", "Markus Höhn", "Daniel Archambault", "M. Lieser", "A. Dalpke", "Simone Scheithauer", "Michael Marschollek", "Vanessa Eichel", "Nico T. Mutters", "Highmed Consortium", "Tatiana von Landesberger" ]	[ "HM" ]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.09552v3", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/Y3fGnxKLFIM", "icon": "video" } ]
VAST	2,020	InCorr: Interactive Data-Driven Correlation Panels for Digital Outcrop Analysis	10.1109/TVCG.2020.3030409	Geological analysis of 3D Digital Outcrop Models (DOMs) for reconstruction of ancient habitable environments is a key aspect of the upcoming ESA ExoMars 2022 Rosalind Franklin Rover and the NASA 2020 Rover Perseverance missions in seeking signs of past life on Mars. Geologists measure and interpret 3D DOMs, create sedi...	false	false	[ "Thomas Ortner", "Andreas Walch", "Rebecca Nowak", "Robert Barnes", "Thomas Höllt", "M. Eduard Gröller" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.11512v2", "icon": "paper" } ]
VAST	2,020	Insight Beyond Numbers: The Impact of Qualitative Factors on Visual Data Analysis	10.1109/TVCG.2020.3030376	As of today, data analysis focuses primarily on the findings to be made inside the data and concentrates less on how those findings relate to the domain of investigation. Contemporary visualization as a field of research shows a strong tendency to adopt this data-centrism. Despite their decisive influence on the analys...	false	false	[ "Benjamin Karer", "Hans Hagen", "Dirk J. Lehmann" ]	[]	[]	[]
VAST	2,020	Integrating Prior Knowledge in Mixed-Initiative Social Network Clustering	10.1109/TVCG.2020.3030347	We propose a new approach-called PK-clustering-to help social scientists create meaningful clusters in social networks. Many clustering algorithms exist but most social scientists find them difficult to understand, and tools do not provide any guidance to choose algorithms, or to evaluate results taking into account th...	false	false	[ "Alexis Pister", "Paolo Buono", "Jean-Daniel Fekete", "Catherine Plaisant", "Paola Valdivia" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2005.02972v2", "icon": "paper" } ]
VAST	2,020	LineSmooth: An Analytical Framework for Evaluating the Effectiveness of Smoothing Techniques on Line Charts	10.1109/TVCG.2020.3030421	We present a comprehensive framework for evaluating line chart smoothing methods under a variety of visual analytics tasks. Line charts are commonly used to visualize a series of data samples. When the number of samples is large, or the data are noisy, smoothing can be applied to make the signal more apparent. However,...	false	false	[ "Paul Rosen 0001", "Ghulam Jilani Quadri" ]	[]	[ "PW", "P", "V", "C" ]	[ { "name": "Project Website with Demo", "url": "https://usfdatavisualization.github.io/LineSmoothDemo/", "icon": "project_website" }, { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.13882v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/K...
VAST	2,020	Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs	10.1109/TVCG.2020.3030398	The overview-driven visual analysis of large-scale dynamic graphs poses a major challenge. We propose Multiscale Snapshots, a visual analytics approach to analyze temporal summaries of dynamic graphs at multiple temporal scales. First, we recursively generate temporal summaries to abstract overlapping sequences of grap...	false	false	[ "Eren Cakmak", "Udo Schlegel", "Dominik Jäckle", "Daniel A. Keim", "Tobias Schreck" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2008.08282v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/qqNPRLmFqDM", "icon": "video" } ]
VAST	2,020	MultiSegVA: Using Visual Analytics to Segment Biologging Time Series on Multiple Scales	10.1109/TVCG.2020.3030386	Segmenting biologging time series of animals on multiple temporal scales is an essential step that requires complex techniques with careful parameterization and possibly cross-domain expertise. Yet, there is a lack of visual-interactive tools that strongly support such multi-scale segmentation. To close this gap, we pr...	false	false	[ "Philipp Meschenmoser", "Juri Buchmüller", "Daniel Seebacher", "Martin Wikelski", "Daniel A. Keim" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.00548v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/Zqqlgv7ZaV0", "icon": "video" } ]
VAST	2,020	Once Upon A Time In Visualization: Understanding the Use of Textual Narratives for Causality	10.1109/TVCG.2020.3030358	Causality visualization can help people understand temporal chains of events, such as messages sent in a distributed system, cause and effect in a historical conflict, or the interplay between political actors over time. However, as the scale and complexity of these event sequences grows, even these visualizations can ...	false	false	[ "Arjun Choudhry", "Mandar Sharma", "Pramod Chundury", "Thomas Kapler", "Derek W. S. Gray", "Naren Ramakrishnan", "Niklas Elmqvist" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02649v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/Ra5hihtc8c0", "icon": "video" } ]
VAST	2,020	P6: A Declarative Language for Integrating Machine Learning in Visual Analytics	10.1109/TVCG.2020.3030453	We present P6, a declarative language for building high performance visual analytics systems through its support for specifying and integrating machine learning and interactive visualization methods. As data analysis methods based on machine learning and artificial intelligence continue to advance, a visual analytics s...	false	false	[ "Jianping Kelvin Li", "Kwan-Liu Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.01399v1", "icon": "paper" } ]
VAST	2,020	PassVizor: Toward Better Understanding of the Dynamics of Soccer Passes	10.1109/TVCG.2020.3030359	In soccer, passing is the most frequent interaction between players and plays a significant role in creating scoring chances. Experts are interested in analyzing players' passing behavior to learn passing tactics, i.e., how players build up an attack with passing. Various approaches have been proposed to facilitate the...	false	false	[ "Xiao Xie", "Jiachen Wang", "Hongye Liang", "Dazhen Deng", "Shoubin Cheng", "Hui Zhang 0051", "Wei Chen 0001", "Yingcai Wu" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02464v1", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/Lr6yuBBrMQw", "icon": "video" } ]
VAST	2,020	PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines	10.1109/TVCG.2020.3030361	In recent years, a wide variety of automated machine learning (AutoML) methods have been proposed to generate end-to-end ML pipelines. While these techniques facilitate the creation of models, given their black-box nature, the complexity of the underlying algorithms, and the large number of pipelines they derive, they ...	false	false	[ "Jorge Henrique Piazentin Ono", "Sonia Castelo", "Roque Lopez", "Enrico Bertini", "Juliana Freire", "Cláudio T. Silva" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2005.00160v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/0FlwKtToYLQ", "icon": "video" } ]
VAST	2,020	Preserving Minority Structures in Graph Sampling	10.1109/TVCG.2020.3030428	Sampling is a widely used graph reduction technique to accelerate graph computations and simplify graph visualizations. By comprehensively analyzing the literature on graph sampling, we assume that existing algorithms cannot effectively preserve minority structures that are rare and small in a graph but are very import...	false	false	[ "Ying Zhao 0001", "Haojin Jiang", "Qi'an Chen", "Yaqi Qin", "Huixuan Xie", "Yitao Wu", "Shixia Liu", "Zhiguang Zhou", "Jiazhi Xia", "Fangfang Zhou" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.02498v2", "icon": "paper" } ]
VAST	2,020	QLens: Visual Analytics of MUlti-step Problem-solving Behaviors for Improving Question Design	10.1109/TVCG.2020.3030337	With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students' ...	false	false	[ "Meng Xia", "Reshika Palaniyappan Velumani", "Yong Wang 0021", "Huamin Qu", "Xiaojuan Ma" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2009.12833v1", "icon": "paper" } ]
VAST	2,020	Revisiting the Modifiable Areal Unit Problem in Deep Traffic Prediction with Visual Analytics	10.1109/TVCG.2020.3030410	Deep learning methods are being increasingly used for urban traffic prediction where spatiotemporal traffic data is aggregated into sequentially organized matrices that are then fed into convolution-based residual neural networks. However, the widely known modifiable areal unit problem within such aggregation processes...	false	false	[ "Wei Zeng 0004", "Chengqiao Lin", "Juncong Lin", "Jincheng Jiang", "Jiazhi Xia", "Cagatay Turkay", "Wei Chen 0001" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.15486v3", "icon": "paper" } ]
VAST	2,020	Selection-Bias-Corrected Visualization via Dynamic Reweighting	10.1109/TVCG.2020.3030455	The collection and visual analysis of large-scale data from complex systems, such as electronic health records or clickstream data, has become increasingly common across a wide range of industries. This type of retrospective visual analysis, however, is prone to a variety of selection bias effects, especially for high-...	false	false	[ "David Borland", "Jonathan Zhang", "Smiti Kaul", "David Gotz" ]	[]	[ "P", "V" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/2007.14964v2", "icon": "paper" }, { "name": "Fast Forward", "url": "https://youtu.be/pqoQZZ07HOo", "icon": "video" } ]

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