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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
VAST	2,017	Analyzing the Training Processes of Deep Generative Models	10.1109/TVCG.2017.2744938	Among the many types of deep models, deep generative models (DGMs) provide a solution to the important problem of unsupervised and semi-supervised learning. However, training DGMs requires more skill, experience, and know-how because their training is more complex than other types of deep models such as convolutional n...	false	false	[ "Mengchen Liu", "Jiaxin Shi", "Kelei Cao", "Jun Zhu 0001", "Shixia Liu" ]	[]	[]	[]
VAST	2,017	Applying Pragmatics Principles for Interaction with Visual Analytics	10.1109/TVCG.2017.2744684	Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to...	false	false	[ "Enamul Hoque", "Vidya Setlur", "Melanie Tory", "Isaac Dykeman" ]	[]	[]	[]
VAST	2,017	Beyond Tasks: An Activity Typology for Visual Analytics	10.1109/TVCG.2017.2745180	As Visual Analytics (VA) research grows and diversifies to encompass new systems, techniques, and use contexts, gaining a holistic view of analytic practices is becoming ever more challenging. However, such a view is essential for researchers and practitioners seeking to develop systems for broad audiences that span mu...	false	false	[ "Darren Edge", "Nathalie Henry Riche", "Jonathan Larson", "Christopher M. White" ]	[]	[]	[]
VAST	2,017	BiDots: Visual Exploration of Weighted Biclusters	10.1109/TVCG.2017.2744458	Discovering and analyzing biclusters, i.e., two sets of related entities with close relationships, is a critical task in many real-world applications, such as exploring entity co-occurrences in intelligence analysis, and studying gene expression in bio-informatics. While the output of biclustering techniques can offer ...	false	false	[ "Jian Zhao 0010", "Maoyuan Sun", "Francine Chen 0001", "Patrick Chiu" ]	[]	[]	[]
VAST	2,017	Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis	10.1109/TVCG.2017.2745181	Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis work...	false	false	[ "Manuel Stein", "Halldór Janetzko", "Andreas Lamprecht", "Thorsten Breitkreutz", "Philipp Zimmermann", "Bastian Goldlücke", "Tobias Schreck", "Gennady L. Andrienko", "Michael Grossniklaus", "Daniel A. Keim" ]	[]	[]	[]
VAST	2,017	Clustering Trajectories by Relevant Parts for Air Traffic Analysis	10.1109/TVCG.2017.2744322	Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. Th...	false	false	[ "Gennady L. Andrienko", "Natalia V. Andrienko", "Georg Fuchs", "Jose Manuel Cordero Garcia" ]	[]	[]	[]
VAST	2,017	Clustervision: Visual Supervision of Unsupervised Clustering	10.1109/TVCG.2017.2745085	Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to re...	false	false	[ "Bum Chul Kwon", "Benjamin Eysenbach", "Janu Verma", "Kenney Ng", "Christopher deFilippi", "Walter F. Stewart", "Adam Perer" ]	[]	[]	[]
VAST	2,017	Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study	10.1109/TVCG.2017.2744818	Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-intera...	false	false	[ "Jürgen Bernard", "Marco Hutter 0002", "Matthias Zeppelzauer", "Dieter W. Fellner", "Michael Sedlmair" ]	[]	[]	[]
VAST	2,017	ConceptVector: Text Visual Analytics via Interactive Lexicon Building Using Word Embedding	10.1109/TVCG.2017.2744478	Central to many text analysis methods is the notion of a concept: a set of semantically related keywords characterizing a specific object, phenomenon, or theme. Advances in word embedding allow building a concept from a small set of seed terms. However, naive application of such techniques may result in false positive ...	false	false	[ "Deok Gun Park 0001", "Seungyeon Kim", "Jurim Lee", "Jaegul Choo", "Nicholas Diakopoulos", "Niklas Elmqvist" ]	[]	[]	[]
VAST	2,017	CRICTO: Supporting Sensemaking through Crowdsourced Information Schematization	10.1109/VAST.2017.8585484	We present CRICTO, a new crowdsourcing visual analytics environment for making sense of and analyzing text data, whereby multiple crowdworkers are able to parallelize the simple information schematization tasks of relating and connecting entities across documents. The diverse links from these schematization tasks are t...	false	false	[ "Haeyong Chung", "Sai Prashanth Dasari", "Santhosh Nandhakumar", "Christopher Andrews" ]	[]	[]	[]
VAST	2,017	CrystalBall: A Visual Analytic System for Future Event Discovery and Analysis from Social Media Data	10.1109/VAST.2017.8585658	Social media data bear valuable insights regarding events that occur around the world. Events are inherently temporal and spatial. Existing visual text analysis systems have focused on detecting and analyzing past and ongoing events. Few have leveraged social media information to look for events that may occur in the f...	false	false	[ "Isaac Cho", "Ryan Wesslen", "Svitlana Volkova", "William Ribarsky", "Wenwen Dou" ]	[]	[]	[]
VAST	2,017	DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks	10.1109/TVCG.2017.2744358	Deep neural networks are now rivaling human accuracy in several pattern recognition problems. Compared to traditional classifiers, where features are handcrafted, neural networks learn increasingly complex features directly from the data. Instead of handcrafting the features, it is now the network architecture that is ...	false	false	[ "Nicola Pezzotti", "Thomas Höllt", "Jan C. van Gemert", "Boudewijn P. F. Lelieveldt", "Elmar Eisemann", "Anna Vilanova" ]	[]	[]	[]
VAST	2,017	Do Convolutional Neural Networks Learn Class Hierarchy?	10.1109/TVCG.2017.2744683	Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visu...	false	false	[ "Bilal Alsallakh", "Amin Jourabloo", "Mao Ye", "Xiaoming Liu 0002", "Ren Liu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1710.06501v1", "icon": "paper" } ]
VAST	2,017	Dynamic Influence Networks for Rule-Based Models	10.1109/TVCG.2017.2745280	We introduce the Dynamic Influence Network (DIN), a novel visual analytics technique for representing and analyzing rule-based models of protein-protein interaction networks. Rule-based modeling has proved instrumental in developing biological models that are concise, comprehensible, easily extensible, and that mitigat...	false	false	[ "Angus G. Forbes", "Andrew Thomas Burks", "Kristine Lee", "Xing Li", "Pierre Boutillier", "Jean Krivine", "Walter Fontana" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1711.00967v1", "icon": "paper" } ]
VAST	2,017	E-Map: A Visual Analytics Approach for Exploring Significant Event Evolutions in Social Media	10.1109/VAST.2017.8585638	Significant events are often discussed and spread through social media, involving many people. Reposting activities and opinions expressed in social media offer good opportunities to understand the evolution of events. However, the dynamics of reposting activities and the diversity of user comments pose challenges to u...	false	false	[ "Siming Chen 0001", "Shuai Chen 0001", "Lijing Lin", "Xiaoru Yuan", "Christy Jie Liang", "Xiaolong Zhang 0001" ]	[]	[]	[]
VAST	2,017	EVA: Visual Analytics to Identify Fraudulent Events	10.1109/TVCG.2017.2744758	Financial institutions are interested in ensuring security and quality for their customers. Banks, for instance, need to identify and stop harmful transactions in a timely manner. In order to detect fraudulent operations, data mining techniques and customer profile analysis are commonly used. However, these approaches ...	false	false	[ "Roger A. Leite", "Theresia Gschwandtner", "Silvia Miksch", "Simone Kriglstein", "Margit Pohl", "Erich Gstrein", "Johannes Kuntner" ]	[]	[]	[]
VAST	2,017	EventThread: Visual Summarization and Stage Analysis of Event Sequence Data	10.1109/TVCG.2017.2745320	Event sequence data such as electronic health records, a person's academic records, or car service records, are ordered series of events which have occurred over a period of time. Analyzing collections of event sequences can reveal common or semantically important sequential patterns. For example, event sequence analys...	false	false	[ "Shunan Guo", "Ke Xu", "Rongwen Zhao", "David Gotz", "Hongyuan Zha", "Nan Cao" ]	[]	[]	[]
VAST	2,017	Graphiti: Interactive Specification of Attribute-Based Edges for Network Modeling and Visualization	10.1109/TVCG.2017.2744843	Network visualizations, often in the form of node-link diagrams, are an effective means to understand relationships between entities, discover entities with interesting characteristics, and to identify clusters. While several existing tools allow users to visualize pre-defined networks, creating these networks from raw...	false	false	[ "Arjun Srinivasan", "Hyunwoo Park", "Alex Endert", "Rahul C. Basole" ]	[]	[]	[]
VAST	2,017	How Do Ancestral Traits Shape Family Trees Over Generations?	10.1109/TVCG.2017.2744080	Whether and how does the structure of family trees differ by ancestral traits over generations? This is a fundamental question regarding the structural heterogeneity of family trees for the multi-generational transmission research. However, previous work mostly focuses on parent-child scenarios due to the lack of prope...	false	false	[ "Siwei Fu", "Hao Dong 0008", "Weiwei Cui", "Jian Zhao 0010", "Huamin Qu" ]	[]	[]	[]
VAST	2,017	Interactive Visual Alignment of Medieval Text Versions	10.1109/VAST.2017.8585505	Textual criticism consists of the identification and analysis of variant readings among different versions of a text. Being a relatively simple task for modern languages, the collation of medieval text traditions ranges from the complex to the virtually impossible depending on the degree of instability of textual trans...	false	false	[ "Stefan Jänicke", "David Joseph Wrisley" ]	[]	[]	[]
VAST	2,017	LDSScanner: Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets	10.1109/TVCG.2017.2744098	Many approaches for analyzing a high-dimensional dataset assume that the dataset contains specific structures, e.g., clusters in linear subspaces or non-linear manifolds. This yields a trial-and-error process to verify the appropriate model and parameters. This paper contributes an exploratory interface that supports v...	false	false	[ "Jiazhi Xia", "Fenjin Ye", "Wei Chen 0001", "Yusi Wang", "Weifeng Chen 0002", "Yuxin Ma", "Anthony K. H. Tung" ]	[]	[]	[]
VAST	2,017	Pattern Trails: Visual Analysis of Pattern Transitions in Subspaces	10.1109/VAST.2017.8585613	Subspace analysis methods have gained interest for identifying patterns in subspaces of high-dimensional data. Existing techniques allow to visualize and compare patterns in subspaces. However, many subspace analysis methods produce an abundant amount of patterns, which often remain redundant and are difficult to relat...	false	false	[ "Dominik Jäckle", "Michael Blumenschein", "Michael Behrisch 0001", "Daniel A. Keim", "Tobias Schreck" ]	[]	[]	[]
VAST	2,017	PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models	10.1109/TVCG.2017.2745118	PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving ...	false	false	[ "Michael Glueck", "Mahdi Pakdaman Naeini", "Finale Doshi-Velez", "Fanny Chevalier", "Azam Khan", "Daniel J. Wigdor", "Michael Brudno" ]	[]	[]	[]
VAST	2,017	Podium: Ranking Data Using Mixed-Initiative Visual Analytics	10.1109/TVCG.2017.2745078	People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importanc...	false	false	[ "Emily Wall", "Subhajit Das 0002", "Ravish Chawla", "Bharath Kalidindi", "Eli T. Brown", "Alex Endert" ]	[]	[]	[]
VAST	2,017	Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework	10.1109/TVCG.2017.2745080	Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement l...	false	false	[ "Mennatallah El-Assady", "Rita Sevastjanova", "Fabian Sperrle", "Daniel A. Keim", "Christopher Collins 0001" ]	[ "HM" ]	[]	[]
VAST	2,017	QSAnglyzer: Visual Analytics for Prismatic Analysis of Question Answering System Evaluations	10.1109/VAST.2017.8585733	Developing sophisticated artificial intelligence (AI) systems requires AI researchers to experiment with different designs and analyze results from evaluations (we refer this task as evaluation analysis). In this paper, we tackle the challenges of evaluation analysis in the domain of question-answering (QA) systems. Th...	false	false	[ "Nan-Chen Chen", "Been Kim" ]	[]	[]	[]
VAST	2,017	Sequence Synopsis: Optimize Visual Summary of Temporal Event Data	10.1109/TVCG.2017.2745083	Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet com...	false	false	[ "Yuanzhe Chen", "Panpan Xu", "Ren Liu" ]	[]	[]	[]
VAST	2,017	SkyLens: Visual Analysis of Skyline on Multi-Dimensional Data	10.1109/TVCG.2017.2744738	Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the ...	false	false	[ "Xun Zhao", "Yanhong Wu", "Weiwei Cui", "Xinnan Du", "Yuan Chen", "Yong Wang 0021", "Dik Lun Lee", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1708.03462v2", "icon": "paper" } ]
VAST	2,017	SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance	10.1109/TVCG.2017.2744805	Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arr...	false	false	[ "Dominik Sacha", "Matthias Kraus", "Jürgen Bernard", "Michael Behrisch 0001", "Tobias Schreck", "Yuki Asano", "Daniel A. Keim" ]	[]	[]	[]
VAST	2,017	Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs	10.1109/TVCG.2017.2745279	During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative ...	false	false	[ "Jian Zhao 0010", "Michael Glueck", "Petra Isenberg", "Fanny Chevalier", "Azam Khan" ]	[ "HM" ]	[]	[]
VAST	2,017	The "y" of it Matters, Even for Storyline Visualization	10.1109/VAST.2017.8585487	Storylines are adept at communicating complex change by encoding time on the x-axis and using the proximity of lines in the y direction to represent interaction between entities. The original definition of a storyline visualization requires data defined in terms of explicit interaction groups. Relaxing this definition ...	false	false	[ "Dustin Arendt", "Meg Pirrung" ]	[]	[]	[]
VAST	2,017	The Anchoring Effect in Decision-Making with Visual Analytics	10.1109/VAST.2017.8585665	Anchoring effect is the tendency to focus too heavily on one piece of information when making decisions. In this paper, we present a novel, systematic study and resulting analyses that investigate the effects of anchoring effect on human decision-making using visual analytic systems. Visual analytics interfaces typical...	false	false	[ "Isaac Cho", "Ryan Wesslen", "Alireza Karduni", "Sashank Santhanam", "Samira Shaikh", "Wenwen Dou" ]	[]	[]	[]
VAST	2,017	The Interactive Visualization Gap in Initial Exploratory Data Analysis	10.1109/TVCG.2017.2743990	Data scientists and other analytic professionals often use interactive visualization in the dissemination phase at the end of a workflow during which findings are communicated to a wider audience. Visualization scientists, however, hold that interactive representation of data can also be used during exploratory analysi...	false	false	[ "Andrea Batch", "Niklas Elmqvist" ]	[]	[]	[]
VAST	2,017	The Role of Explicit Knowledge: A Conceptual Model of Knowledge-Assisted Visual Analytics	10.1109/VAST.2017.8585498	Visual Analytics (VA) aims to combine the strengths of humans and computers for effective data analysis. In this endeavor, humans' tacit knowledge from prior experience is an important asset that can be leveraged by both human and computer to improve the analytic process. While VA environments are starting to include f...	false	false	[ "Paolo Federico 0001", "Markus Wagner 0008", "Alexander Rind", "Albert Amor-Amoros", "Silvia Miksch", "Wolfgang Aigner" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://research.fhstp.ac.at/content/download/89486/file/federico-wagner_2017_knava-model.pdf", "icon": "paper" } ]
VAST	2,017	Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics	10.1109/TVCG.2017.2745258	Dimension reduction algorithms and clustering algorithms are both frequently used techniques in visual analytics. Both families of algorithms assist analysts in performing related tasks regarding the similarity of observations and finding groups in datasets. Though initially used independently, recent works have incorp...	false	false	[ "John E. Wenskovitch", "Ian Crandell", "Naren Ramakrishnan", "Leanna House", "Scotland Leman", "Chris North 0001" ]	[]	[]	[]
VAST	2,017	TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees	10.1109/TVCG.2017.2745158	Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware mod...	false	false	[ "Thomas Mühlbacher", "Lorenz Linhardt", "Torsten Möller", "Harald Piringer" ]	[]	[]	[]
VAST	2,017	Understanding a Sequence of Sequences: Visual Exploration of Categorical States in Lake Sediment Cores	10.1109/TVCG.2017.2744686	This design study focuses on the analysis of a time sequence of categorical sequences. Such data is relevant for the geoscientific research field of landscape and climate development. It results from microscopic analysis of lake sediment cores. The goal is to gain hypotheses about landscape evolution and climate condit...	false	false	[ "Andrea Unger", "Nadine Drager", "Mike Sips", "Dirk J. Lehmann" ]	[]	[]	[]
VAST	2,017	Understanding Hidden Memories of Recurrent Neural Networks	10.1109/VAST.2017.8585721	Recurrent neural networks (RNNs) have been successfully applied to various natural language processing (NLP) tasks and achieved better results than conventional methods. However, the lack of understanding of the mechanisms behind their effectiveness limits further improvements on their architectures. In this paper, we ...	false	false	[ "Yao Ming", "Shaozu Cao", "Ruixiang Zhang", "Zhen Li 0044", "Yuanzhe Chen", "Yangqiu Song", "Huamin Qu" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1710.10777v1", "icon": "paper" } ]
VAST	2,017	Understanding the Relationship Between Interactive Optimisation and Visual Analytics in the Context of Prostate Brachytherapy	10.1109/TVCG.2017.2744418	The fields of operations research and computer science have long sought to find automatic solver techniques that can find high-quality solutions to difficult real-world optimisation problems. The traditional workflow is to exactly model the problem and then enter this model into a general-purpose “black-box” solver. In...	false	false	[ "Jie Liu", "Tim Dwyer", "Kim Marriott", "Jeremy Millar", "Annette Haworth" ]	[]	[]	[]
VAST	2,017	VIGOR: Interactive Visual Exploration of Graph Query Results	10.1109/TVCG.2017.2744898	Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analys...	false	false	[ "Robert S. Pienta", "Fred Hohman", "Alex Endert", "Acar Tamersoy", "Kevin A. Roundy", "Christopher Gates 0002", "Shamkant B. Navathe", "Polo Chau" ]	[]	[]	[]
VAST	2,017	Visual Causality Analysis Made Practical	10.1109/VAST.2017.8585647	Deriving the exact casual model that governs the relations between variables in a multidimensional dataset is difficult in practice. It is because causal inference algorithms by themselves typically cannot encode an adequate amount of domain knowledge to break all ties. Visual analytic approaches are considered a feasi...	false	false	[ "Jun Wang", "Klaus Mueller 0001" ]	[]	[]	[]
VAST	2,017	Visual Diagnosis of Tree Boosting Methods	10.1109/TVCG.2017.2744378	Tree boosting, which combines weak learners (typically decision trees) to generate a strong learner, is a highly effective and widely used machine learning method. However, the development of a high performance tree boosting model is a time-consuming process that requires numerous trial-and-error experiments. To tackle...	false	false	[ "Shixia Liu", "Jiannan Xiao", "Junlin Liu", "Xiting Wang", "Jing Wu 0004", "Jun Zhu 0001" ]	[]	[]	[]
VAST	2,017	Visualizing Big Data Outliers Through Distributed Aggregation	10.1109/TVCG.2017.2744685	Visualizing outliers in massive datasets requires statistical pre-processing in order to reduce the scale of the problem to a size amenable to rendering systems like D3, Plotly or analytic systems like R or SAS. This paper presents a new algorithm, calledhdoutliers, for detecting multidimensional outliers. It is unique...	false	false	[ "Leland Wilkinson" ]	[]	[]	[]
VAST	2,017	Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses	10.1109/TVCG.2017.2745178	In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensi...	false	false	[ "Alexander Kumpf", "Bianca Tost", "Marlene Baumgart", "Michael Riemer", "Rüdiger Westermann", "Marc Rautenhaus" ]	[]	[]	[]
VAST	2,017	Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow	10.1109/TVCG.2017.2744878	We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard l...	false	false	[ "Kanit Wongsuphasawat", "Daniel Smilkov", "James Wexler", "Jimbo Wilson", "Dan Mané", "Doug Fritz", "Dilip Krishnan", "Fernanda B. Viégas", "Martin Wattenberg" ]	[ "BP" ]	[]	[]
VAST	2,017	Visualizing Real-Time Strategy Games: The Example of StarCraft II	10.1109/VAST.2017.8585594	We present a visualization system for users to examine real-time strategy games, which have become very popular globally in recent years. Unlike previous systems that focus on showing statistics and build order, our system can depict the most important part - battles in the games. Specifically, we visualize detailed mo...	false	false	[ "Yen-Ting Kuan", "Yu-Shuen Wang", "Jung-Hong Chuang" ]	[]	[]	[]
VAST	2,017	Voila: Visual Anomaly Detection and Monitoring with Streaming Spatiotemporal Data	10.1109/TVCG.2017.2744419	The increasing availability of spatiotemporal data continuously collected from various sources provides new opportunities for a timely understanding of the data in their spatial and temporal context. Finding abnormal patterns in such data poses significant challenges. Given that there is often no clear boundary between...	false	false	[ "Nan Cao", "Chaoguang Lin", "Qiuhan Zhu", "Yu-Ru Lin", "Xian Teng", "Xidao Wen" ]	[]	[]	[]
VAST	2,017	Warning, Bias May Occur: A Proposed Approach to Detecting Cognitive Bias in Interactive Visual Analytics	10.1109/VAST.2017.8585669	Visual analytic tools combine the complementary strengths of humans and machines in human-in-the-loop systems. Humans provide invaluable domain expertise and sensemaking capabilities to this discourse with analytic models; however, little consideration has yet been given to the ways inherent human biases might shape th...	false	false	[ "Emily Wall", "Leslie M. Blaha", "Lyndsey Franklin", "Alex Endert" ]	[]	[]	[]
SciVis	2,017	A Virtual Reality Visualization Tool for Neuron Tracing	10.1109/TVCG.2017.2744079	Tracing neurons in large-scale microscopy data is crucial to establishing a wiring diagram of the brain, which is needed to understand how neural circuits in the brain process information and generate behavior. Automatic techniques often fail for large and complex datasets, and connectomics researchers may spend weeks ...	false	false	[ "Will Usher 0001", "Pavol Klacansky", "Frederick Federer", "Peer-Timo Bremer", "Aaron Knoll", "Jeff Yarch", "Alessandra Angelucci", "Valerio Pascucci" ]	[]	[]	[]
SciVis	2,017	Abstractocyte: A Visual Tool for Exploring Nanoscale Astroglial Cells	10.1109/TVCG.2017.2744278	This paper presents Abstractocyte, a system for the visual analysis of astrocytes and their relation to neurons, in nanoscale volumes of brain tissue. Astrocytes are glial cells, i.e., non-neuronal cells that support neurons and the nervous system. The study of astrocytes has immense potential for understanding brain f...	false	false	[ "Haneen Mohammed", "Ali K. Al-Awami", "Johanna Beyer", "Corrado Calì", "Pierre J. Magistretti", "Hanspeter Pfister", "Markus Hadwiger" ]	[]	[]	[]
SciVis	2,017	Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization	10.1109/TVCG.2017.2744459	Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven vis...	false	false	[ "G. Elisabeta Marai" ]	[]	[]	[]
SciVis	2,017	An Intelligent System Approach for Probabilistic Volume Rendering Using Hierarchical 3D Convolutional Sparse Coding	10.1109/TVCG.2017.2744078	In this paper, we propose a novel machine learning-based voxel classification method for highly-accurate volume rendering. Unlike conventional voxel classification methods that incorporate intensity-based features, the proposed method employs dictionary based features learned directly from the input data using hierarch...	false	false	[ "Tran Minh Quan", "Junyoung Choi", "Haejin Jeong", "Won-Ki Jeong" ]	[]	[]	[]
SciVis	2,017	BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI	10.1109/TVCG.2017.2744479	Mass spectrometry imaging (MSI) is a transformative imaging method that supports the untargeted, quantitative measurement of the chemical composition and spatial heterogeneity of complex samples with broad applications in life sciences, bioenergy, and health. While MSI data can be routinely collected, its broad applica...	false	false	[ "Oliver Rübel", "Benjamin P. Bowen" ]	[]	[]	[]
SciVis	2,017	Clique Community Persistence: A Topological Visual Analysis Approach for Complex Networks	10.1109/TVCG.2017.2744321	Complex networks require effective tools and visualizations for their analysis and comparison. Clique communities have been recognized as a powerful concept for describing cohesive structures in networks. We propose an approach that extends the computation of clique communities by considering persistent homology, a top...	false	false	[ "Bastian Rieck", "Ulderico Fugacci", "Jonas Lukasczyk", "Heike Leitte" ]	[]	[]	[]
SciVis	2,017	Decision Graph Embedding for High-Resolution Manometry Diagnosis	10.1109/TVCG.2017.2744299	High-resolution manometry is an imaging modality which enables the categorization of esophageal motility disorders. Spatio-temporal pressure data along the esophagus is acquired using a tubular device and multiple test swallows are performed by the patient. Current approaches visualize these swallows as individual inst...	false	false	[ "Julian Kreiser", "Alexander Hann", "Eugen Zizer", "Timo Ropinski" ]	[]	[]	[]
SciVis	2,017	Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing	10.1109/TVCG.2017.2744059	We propose a dynamically load-balanced algorithm for parallel particle tracing, which periodically attempts to evenly redistribute particles across processes based on k-d tree decomposition. Each process is assigned with (1) a statically partitioned, axis-aligned data block that partially overlaps with neighboring bloc...	false	false	[ "Jiang Zhang 0002", "Hanqi Guo 0001", "Fan Hong", "Xiaoru Yuan", "Tom Peterka" ]	[]	[]	[]
SciVis	2,017	Globe Browsing: Contextualized Spatio-Temporal Planetary Surface Visualization	10.1109/TVCG.2017.2743958	Results of planetary mapping are often shared openly for use in scientific research and mission planning. In its raw format, however, the data is not accessible to non-experts due to the difficulty in grasping the context and the intricate acquisition process. We present work on tailoring and integration of multiple da...	false	false	[ "Karl Bladin", "Emil Axelsson", "Erik Broberg", "Carter Emmart", "Patric Ljung", "Alexander Bock 0002", "Anders Ynnerman" ]	[ "BP" ]	[]	[]
SciVis	2,017	Instant Construction and Visualization of Crowded Biological Environments	10.1109/TVCG.2017.2744258	We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a...	false	false	[ "Tobias Klein", "Ludovic Autin", "Barbora Kozlíková", "David S. Goodsell", "Arthur J. Olson", "M. Eduard Gröller", "Ivan Viola" ]	[ "HM" ]	[]	[]
SciVis	2,017	Interactive Design and Visualization of Branched Covering Spaces	10.1109/TVCG.2017.2744038	Branched covering spaces are a mathematical concept which originates from complex analysis and topology and has applications in tensor field topology and geometry remeshing. Given a manifold surface and an$N$-way rotational symmetry field, a branched covering space is a manifold surface that has an$N$-to-1 map to the o...	false	false	[ "Lawrence Roy", "Prashant Kumar", "Sanaz Golbabaei", "Yue Zhang 0009", "Eugene Zhang" ]	[]	[]	[]
SciVis	2,017	Interactive Dynamic Volume Illumination with Refraction and Caustics	10.1109/TVCG.2017.2744438	In recent years, significant progress has been made in developing high-quality interactive methods for realistic volume illumination. However, refraction - despite being an important aspect of light propagation in participating media - has so far only received little attention. In this paper, we present a novel approac...	false	false	[ "Jens G. Magnus", "Stefan Bruckner" ]	[]	[]	[]
SciVis	2,017	Multiscale Visualization and Scale-Adaptive Modification of DNA Nanostructures	10.1109/TVCG.2017.2743981	We present an approach to represent DNA nanostructures in varying forms of semantic abstraction, describe ways to smoothly transition between them, and thus create a continuous multiscale visualization and interaction space for applications in DNA nanotechnology. This new way of observing, interacting with, and creatin...	false	false	[ "Haichao Miao", "Elisa De Llano", "Johannes Sorger", "Yasaman Ahmadi", "Tadija Kekic", "Tobias Isenberg 0001", "M. Eduard Gröller", "Ivan Barisic", "Ivan Viola" ]	[]	[]	[]
SciVis	2,017	On the Treatment of Field Quantities and Elemental Continuity in FEM Solutions	10.1109/TVCG.2017.2744058	As the finite element method (FEM) and the finite volume method (FVM), both traditional and high-order variants, continue their proliferation into various applied engineering disciplines, it is important that the visualization techniques and corresponding data analysis tools that act on the results produced by these me...	false	false	[ "Ashok Jallepalli", "Julia Docampo-Sánchez", "Jennifer K. Ryan", "Robert Haimes", "Robert M. Kirby" ]	[]	[]	[]
SciVis	2,017	Robust Detection and Visualization of Jet-Stream Core Lines in Atmospheric Flow	10.1109/TVCG.2017.2743989	Jet-streams, their core lines and their role in atmospheric dynamics have been subject to considerable meteorological research since the first half of the twentieth century. Yet, until today no consistent automated feature detection approach has been proposed to identify jet-stream core lines from 3D wind fields. Such ...	false	false	[ "Michael Kern", "Tim Hewson", "Filip Sadlo", "Rüdiger Westermann", "Marc Rautenhaus" ]	[]	[]	[]
SciVis	2,017	Screen-Space Normal Distribution Function Caching for Consistent Multi-Resolution Rendering of Large Particle Data	10.1109/TVCG.2017.2743979	Molecular dynamics (MD) simulations are crucial to investigating important processes in physics and thermodynamics. The simulated atoms are usually visualized as hard spheres with Phong shading, where individual particles and their local density can be perceived well in close-up views. However, for large-scale simulati...	false	false	[ "Mohamed Ibrahim", "Patrick Wickenhauser", "Peter Rautek", "Guido Reina", "Markus Hadwiger" ]	[]	[]	[]
SciVis	2,017	SparseLeap: Efficient Empty Space Skipping for Large-Scale Volume Rendering	10.1109/TVCG.2017.2744238	Recent advances in data acquisition produce volume data of very high resolution and large size, such as terabyte-sized microscopy volumes. These data often contain many fine and intricate structures, which pose huge challenges for volume rendering, and make it particularly important to efficiently skip empty space. Thi...	false	false	[ "Markus Hadwiger", "Ali K. Al-Awami", "Johanna Beyer", "Marco Agus", "Hanspeter Pfister" ]	[]	[]	[]
SciVis	2,017	StreetVizor: Visual Exploration of Human-Scale Urban Forms Based on Street Views	10.1109/TVCG.2017.2744159	Urban forms at human-scale, i.e., urban environments that individuals can sense (e.g., sight, smell, and touch) in their daily lives, can provide unprecedented insights on a variety of applications, such as urban planning and environment auditing. The analysis of urban forms can help planners develop high-quality urban...	false	false	[ "Qiaomu Shen", "Wei Zeng 0004", "Yu Ye", "Stefan Müller Arisona", "Simon Schubiger-Banz", "Remo Aslak Burkhard", "Huamin Qu" ]	[]	[]	[]
SciVis	2,017	The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps	10.1109/TVCG.2017.2743978	A myriad of design rules for what constitutes a “good” colormap can be found in the literature. Some common rules include order, uniformity, and high discriminative power. However, the meaning of many of these terms is often ambiguous or open to interpretation. At times, different authors may use the same term to descr...	false	false	[ "Roxana Bujack", "Terece L. Turton", "Francesca Samsel", "Colin Ware", "David H. Rogers 0001", "James P. Ahrens" ]	[]	[]	[]
SciVis	2,017	The Topology ToolKit	10.1109/TVCG.2017.2743938	This system paper presents the Topology ToolKit (TTK), a software platform designed for the topological analysis of scalar data in scientific visualization. While topological data analysis has gained in popularity over the last two decades, it has not yet been widely adopted as a standard data analysis tool for end use...	false	false	[ "Julien Tierny", "Guillaume Favelier", "Joshua A. Levine", "Charles Gueunet", "Michael Michaux" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1805.09110v2", "icon": "paper" } ]
SciVis	2,017	TopoAngler: Interactive Topology-Based Extraction of Fishes	10.1109/TVCG.2017.2743980	We present TopoAngler, a visualization framework that enables an interactive user-guided segmentation of fishes contained in a micro-CT scan. The inherent noise in the CT scan coupled with the often disconnected (and sometimes broken) skeletal structure of fishes makes an automatic segmentation of the volume impractica...	false	false	[ "Alexander Bock 0002", "Harish Doraiswamy", "Adam Summers", "Cláudio T. Silva" ]	[]	[]	[]
SciVis	2,017	Uncertainty Visualization Using Copula-Based Analysis in Mixed Distribution Models	10.1109/TVCG.2017.2744099	Distributions are often used to model uncertainty in many scientific datasets. To preserve the correlation among the spatially sampled grid locations in the dataset, various standard multivariate distribution models have been proposed in visualization literature. These models treat each grid location as a univariate ra...	false	false	[ "Subhashis Hazarika", "Ayan Biswas", "Han-Wei Shen" ]	[]	[]	[]
SciVis	2,017	Visualization Multi-Pipeline for Communicating Biology	10.1109/TVCG.2017.2744518	We propose a system to facilitate biology communication by developing a pipeline to support the instructional visualization of heterogeneous biological data on heterogeneous user-devices. Discoveries and concepts in biology are typically summarized with illustrations assembled manually from the interpretation and appli...	false	false	[ "Peter Mindek", "David Kouril", "Johannes Sorger", "Daniel Toloudis", "Blair Lyons", "Graham Johnson", "M. Eduard Gröller", "Ivan Viola" ]	[]	[]	[]
InfoVis	2,017	Active Reading of Visualizations	10.1109/TVCG.2017.2745958	We investigate whether the notion of active reading for text might be usefully applied to visualizations. Through a qualitative study we explored whether people apply observable active reading techniques when reading paper-based node-link visualizations. Participants used a range of physical actions while reading, and ...	false	false	[ "Jagoda Walny", "Samuel Huron", "Charles Perin", "Tiffany Wun", "Richard Pusch", "Sheelagh Carpendale" ]	[]	[]	[]
InfoVis	2,017	Assessing the Graphical Perception of Time and Speed on 2D+Time Trajectories	10.1109/TVCG.2017.2743918	We empirically evaluate the extent to which people perceive non-constant time and speed encoded on 2D paths. In our graphical perception study, we evaluate nine encodings from the literature for both straight and curved paths. Visualizing time and speed information is a challenge when the x and y axes already encode ot...	false	false	[ "Charles Perin", "Tiffany Wun", "Richard Pusch", "Sheelagh Carpendale" ]	[]	[]	[]
InfoVis	2,017	Blinded with Science or Informed by Charts? A Replication Study	10.1109/TVCG.2017.2744298	We provide a reappraisal of Tal and Wansink's study “Blinded with Science”, where seemingly trivial charts were shown to increase belief in drug efficacy, presumably because charts are associated with science. Through a series of four replications conducted on two crowdsourcing platforms, we investigate an alternative ...	false	false	[ "Pierre Dragicevic", "Yvonne Jansen" ]	[]	[]	[]
InfoVis	2,017	Bridging from Goals to Tasks with Design Study Analysis Reports	10.1109/TVCG.2017.2744319	Visualization researchers and practitioners engaged in generating or evaluating designs are faced with the difficult problem of transforming the questions asked and actions taken by target users from domain-specific language and context into more abstract forms. Existing abstract task classifications aim to provide sup...	false	false	[ "Heidi Lam", "Melanie Tory", "Tamara Munzner" ]	[ "HM" ]	[]	[]
InfoVis	2,017	Bubble Treemaps for Uncertainty Visualization	10.1109/TVCG.2017.2743959	We present a novel type of circular treemap, where we intentionally allocate extra space for additional visual variables. With this extended visual design space, we encode hierarchically structured data along with their uncertainties in a combined diagram. We introduce a hierarchical and force-based circle-packing algo...	false	false	[ "Jochen Görtler", "Christoph Schulz 0001", "Daniel Weiskopf", "Oliver Deussen" ]	[]	[]	[]
InfoVis	2,017	CasCADe: A Novel 4D Visualization System for Virtual Construction Planning	10.1109/TVCG.2017.2745105	Building Information Modeling (BIM) provides an integrated 3D environment to manage large-scale engineering projects. The Architecture, Engineering and Construction (AEC) industry explores 4D visualizations over these datasets for virtual construction planning. However, existing solutions lack adequate visual mechanism...	false	false	[ "Paulo Ivson 0001", "Daniel Nascimento", "Waldemar Celes Filho", "Simone D. J. Barbosa" ]	[]	[]	[]
InfoVis	2,017	Conceptual and Methodological Issues in Evaluating Multidimensional Visualizations for Decision Support	10.1109/TVCG.2017.2745138	We explore how to rigorously evaluate multidimensional visualizations for their ability to support decision making. We first define multi-attribute choice tasks, a type of decision task commonly performed with such visualizations. We then identify which of the existing multidimensional visualizations are compatible wit...	false	false	[ "Evanthia Dimara", "Anastasia Bezerianos", "Pierre Dragicevic" ]	[]	[]	[]
InfoVis	2,017	Considerations for Visualizing Comparison	10.1109/TVCG.2017.2744199	Supporting comparison is a common and diverse challenge in visualization. Such support is difficult to design because solutions must address both the specifics of their scenario as well as the general issues of comparison. This paper aids designers by providing a strategy for considering those general issues. It presen...	false	false	[ "Michael Gleicher" ]	[]	[]	[]
InfoVis	2,017	CyteGuide: Visual Guidance for Hierarchical Single-Cell Analysis	10.1109/TVCG.2017.2744318	Single-cell analysis through mass cytometry has become an increasingly important tool for immunologists to study the immune system in health and disease. Mass cytometry creates a high-dimensional description vector for single cells by time-of-flight measurement. Recently, t-Distributed Stochastic Neighborhood Embedding...	false	false	[ "Thomas Höllt", "Nicola Pezzotti", "Vincent van Unen", "Frits Koning", "Boudewijn P. F. Lelieveldt", "Anna Vilanova" ]	[]	[]	[]
InfoVis	2,017	Data Through Others' Eyes: The Impact of Visualizing Others' Expectations on Visualization Interpretation	10.1109/TVCG.2017.2745240	In addition to visualizing input data, interactive visualizations have the potential to be social artifacts that reveal other people's perspectives on the data. However, how such social information embedded in a visualization impacts a viewer's interpretation of the data remains unknown. Inspired by recent interactive ...	false	false	[ "Yea-Seul Kim", "Katharina Reinecke", "Jessica Hullman" ]	[]	[]	[]
InfoVis	2,017	Data Visualization Saliency Model: A Tool for Evaluating Abstract Data Visualizations	10.1109/TVCG.2017.2743939	Evaluating the effectiveness of data visualizations is a challenging undertaking and often relies on one-off studies that test a visualization in the context of one specific task. Researchers across the fields of data science, visualization, and human-computer interaction are calling for foundational tools and principl...	false	false	[ "Laura E. Matzen", "Michael J. Haass", "Kristin Divis", "Zhiyuan Wang", "Andrew T. Wilson" ]	[]	[]	[]
InfoVis	2,017	EdWordle: Consistency-Preserving Word Cloud Editing	10.1109/TVCG.2017.2745859	We present EdWordle, a method for consistently editing word clouds. At its heart, EdWordle allows users to move and edit words while preserving the neighborhoods of other words. To do so, we combine a constrained rigid body simulation with a neighborhood-aware local Wordle algorithm to update the cloud and to create ve...	false	false	[ "Yunhai Wang", "Xiaowei Chu", "Chen Bao", "Lifeng Zhu", "Oliver Deussen", "Baoquan Chen", "Michael Sedlmair" ]	[]	[]	[]
InfoVis	2,017	Exploring Multivariate Event Sequences Using Rules, Aggregations, and Selections	10.1109/TVCG.2017.2745278	Multivariate event sequences are ubiquitous: travel history, telecommunication conversations, and server logs are some examples. Besides standard properties such as type and timestamp, events often have other associated multivariate data. Current exploration and analysis methods either focus on the temporal analysis of...	false	false	[ "Bram C. M. Cappers", "Jarke J. van Wijk" ]	[]	[]	[]
InfoVis	2,017	Extracting and Retargeting Color Mappings from Bitmap Images of Visualizations	10.1109/TVCG.2017.2744320	Visualization designers regularly use color to encode quantitative or categorical data. However, visualizations “in the wild” often violate perceptual color design principles and may only be available as bitmap images. In this work, we contribute a method to semi-automatically extract color encodings from a bitmap visu...	false	false	[ "Jorge Poco", "Angela Mayhua", "Jeffrey Heer" ]	[]	[]	[]
InfoVis	2,017	Functional Decomposition for Bundled Simplification of Trail Sets	10.1109/TVCG.2017.2744338	Bundling visually aggregates curves to reduce clutter and help finding important patterns in trail-sets or graph drawings. We propose a new approach to bundling based on functional decomposition of the underling dataset. We recover the functional nature of the curves by representing them as linear combinations of piece...	false	false	[ "Christophe Hurter", "Stéphane Puechmorel", "Florence Nicol", "Alexandru C. Telea" ]	[]	[]	[]
InfoVis	2,017	HiPiler: Visual Exploration of Large Genome Interaction Matrices with Interactive Small Multiples	10.1109/TVCG.2017.2745978	This paper presents an interactive visualization interface-HiPiler-for the exploration and visualization of regions-of-interest in large genome interaction matrices. Genome interaction matrices approximate the physical distance of pairs of regions on the genome to each other and can contain up to 3 million rows and col...	false	false	[ "Fritz Lekschas", "Benjamin Bach", "Peter Kerpedjiev", "Nils Gehlenborg", "Hanspeter Pfister" ]	[]	[]	[]
InfoVis	2,017	Imagining Replications: Graphical Prediction & Discrete Visualizations Improve Recall & Estimation of Effect Uncertainty	10.1109/TVCG.2017.2743898	People often have erroneous intuitions about the results of uncertain processes, such as scientific experiments. Many uncertainty visualizations assume considerable statistical knowledge, but have been shown to prompt erroneous conclusions even when users possess this knowledge. Active learning approaches been shown to...	false	false	[ "Jessica Hullman", "Matthew Kay 0001", "Yea-Seul Kim", "Samana Shrestha" ]	[]	[]	[]
InfoVis	2,017	iTTVis: Interactive Visualization of Table Tennis Data	10.1109/TVCG.2017.2744218	The rapid development of information technology paved the way for the recording of fine-grained data, such as stroke techniques and stroke placements, during a table tennis match. This data recording creates opportunities to analyze and evaluate matches from new perspectives. Nevertheless, the increasingly complex data...	false	false	[ "Yingcai Wu", "Ji Lan", "Xinhuan Shu", "Chenyang Ji", "Kejian Zhao", "Jiachen Wang", "Hui Zhang 0051" ]	[]	[]	[]
InfoVis	2,017	Keeping Multiple Views Consistent: Constraints, Validations, and Exceptions in Visualization Authoring	10.1109/TVCG.2017.2744198	Visualizations often appear in multiples, either in a single display (e.g., small multiples, dashboard) or across time or space (e.g., slideshow, set of dashboards). However, existing visualization design guidelines typically focus on single rather than multiple views. Solely following these guidelines can lead to effe...	false	false	[ "Zening Qu", "Jessica Hullman" ]	[ "HM" ]	[ "P" ]	[ { "name": "Paper Preprint", "url": "https://osf.io/zm4ub", "icon": "paper" } ]
InfoVis	2,017	LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks	10.1109/TVCG.2017.2744158	Recurrent neural networks, and in particular long short-term memory (LSTM) networks, are a remarkably effective tool for sequence modeling that learn a dense black-box hidden representation of their sequential input. Researchers interested in better understanding these models have studied the changes in hidden state re...	false	false	[ "Hendrik Strobelt", "Sebastian Gehrmann", "Hanspeter Pfister", "Alexander M. Rush" ]	[]	[ "P" ]	[ { "name": "Paper Preprint", "url": "http://arxiv.org/pdf/1606.07461v2", "icon": "paper" } ]
InfoVis	2,017	Modeling Color Difference for Visualization Design	10.1109/TVCG.2017.2744359	Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured using large, unifor...	false	false	[ "Danielle Albers Szafir" ]	[ "BP" ]	[]	[]
InfoVis	2,017	MyBrush: Brushing and Linking with Personal Agency	10.1109/TVCG.2017.2743859	We extend the popular brushing and linking technique by incorporating personal agency in the interaction. We map existing research related to brushing and linking into a design space that deconstructs the interaction technique into three components: source (what is being brushed), link (the expression of relationship b...	false	false	[ "Philipp Koytek", "Charles Perin", "Jo Vermeulen", "Elisabeth André", "Sheelagh Carpendale" ]	[]	[]	[]
InfoVis	2,017	Nonlinear Dot Plots	10.1109/TVCG.2017.2744018	Conventional dot plots use a constant dot size and are typically applied to show the frequency distribution of small data sets. Unfortunately, they are not designed for a high dynamic range of frequencies. We address this problem by introducing nonlinear dot plots. Adopting the idea of nonlinear scaling from logarithmi...	false	false	[ "Nils Rodrigues", "Daniel Weiskopf" ]	[]	[]	[]
InfoVis	2,017	Open vs. Closed Shapes: New Perceptual Categories?	10.1109/TVCG.2017.2745086	Effective communication using visualization relies in part on the use of viable encoding strategies. For example, a viewer's ability to rapidly and accurately discern between two or more categorical variables in a chart or figure is contingent upon the distinctiveness of the encodings applied to each variable. Research...	false	false	[ "David Burlinson", "Kalpathi R. Subramanian", "Paula Goolkasian" ]	[]	[]	[]
InfoVis	2,017	Orko: Facilitating Multimodal Interaction for Visual Exploration and Analysis of Networks	10.1109/TVCG.2017.2745219	Data visualization systems have predominantly been developed for WIMP-based direct manipulation interfaces. Only recently have other forms of interaction begun to appear, such as natural language or touch-based interaction, though usually operating only independently. Prior evaluations of natural language interfaces fo...	false	false	[ "Arjun Srinivasan", "John T. Stasko" ]	[]	[]	[]
InfoVis	2,017	Priming and Anchoring Effects in Visualization	10.1109/TVCG.2017.2744138	We investigate priming and anchoring effects on perceptual tasks in visualization. Priming or anchoring effects depict the phenomena that a stimulus might influence subsequent human judgments on a perceptual level, or on a cognitive level by providing a frame of reference. Using visual class separability in scatterplot...	false	false	[ "André Calero Valdez", "Martina Ziefle", "Michael Sedlmair" ]	[]	[]	[]
InfoVis	2,017	Revisiting Stress Majorization as a Unified Framework for Interactive Constrained Graph Visualization	10.1109/TVCG.2017.2745919	We present an improved stress majorization method that incorporates various constraints, including directional constraints without the necessity of solving a constraint optimization problem. This is achieved by reformulating the stress function to impose constraints on both the edge vectors and lengths instead of just ...	false	false	[ "Yunhai Wang", "Yanyan Wang", "Yinqi Sun", "Lifeng Zhu", "Kecheng Lu", "Chi-Wing Fu", "Michael Sedlmair", "Oliver Deussen", "Baoquan Chen" ]	[]	[]	[]
InfoVis	2,017	Scatterplots: Tasks, Data, and Designs	10.1109/TVCG.2017.2744184	Traditional scatterplots fail to scale as the complexity and amount of data increases. In response, there exist many design options that modify or expand the traditional scatterplot design to meet these larger scales. This breadth of design options creates challenges for designers and practitioners who must select appr...	false	false	[ "Alper Sarikaya", "Michael Gleicher" ]	[]	[]	[]
InfoVis	2,017	Skeleton-Based Scagnostics	10.1109/TVCG.2017.2744339	Scatterplot matrices (SPLOMs) are widely used for exploring multidimensional data. Scatterplot diagnostics (scagnostics) approaches measure characteristics of scatterplots to automatically find potentially interesting plots, thereby making SPLOMs more scalable with the dimension count. While statistical measures such a...	false	false	[ "José Matute", "Alexandru C. Telea", "Lars Linsen" ]	[]	[]	[]

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