Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1301.3516	Learnable Pooling Regions for Image Classification	Biologically inspired, from the early HMAX model to Spatial Pyramid Matching, pooling has played an important role in visual recognition pipelines. Spatial pooling, by grouping of local codes, equips these methods with a certain degree of robustness to translation and deformation yet preserving important spatial inform...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	21,094
2205.05907	Machine Learning Workflow to Explain Black-box Models for Early Alzheimer's Disease Classification Evaluated for Multiple Datasets	Purpose: Hard-to-interpret Black-box Machine Learning (ML) were often used for early Alzheimer's Disease (AD) detection. Methods: To interpret eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM) black-box models a workflow based on Shapley values was developed. All models were tr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	296,081
2407.10978	Building Artificial Intelligence with Creative Agency and Self-hood	This paper is an invited layperson summary for The Academic of the paper referenced on the last page. We summarize how the formal framework of autocatalytic networks offers a means of modeling the origins of self-organizing, self-sustaining structures that are sufficiently complex to reproduce and evolve, be they organ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	473,212
2405.13832	Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review	Data privacy has become a major concern in healthcare due to the increasing digitization of medical records and data-driven medical research. Protecting sensitive patient information from breaches and unauthorized access is critical, as such incidents can have severe legal and ethical complications. Federated Learning ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	456,102
2407.04551	An AI Architecture with the Capability to Classify and Explain Hardware Trojans	Hardware trojan detection methods, based on machine learning (ML) techniques, mainly identify suspected circuits but lack the ability to explain how the decision was arrived at. An explainable methodology and architecture is introduced based on the existing hardware trojan detection features. Results are provided for e...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	470,607
2211.16855	ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging with Adaptive Threshold	Tomographic SAR technique has attracted remarkable interest for its ability of three-dimensional resolving along the elevation direction via a stack of SAR images collected from different cross-track angles. The emerged compressed sensing (CS)-based algorithms have been introduced into TomoSAR considering its super-res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,776
2205.07680	BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models	Image-to-image translation is an important and challenging problem in computer vision and image processing. Diffusion models (DM) have shown great potentials for high-quality image synthesis, and have gained competitive performance on the task of image-to-image translation. However, most of the existing diffusion model...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,680
2303.07194	Neural Partial Differential Equations with Functional Convolution	We present a lightweighted neural PDE representation to discover the hidden structure and predict the solution of different nonlinear PDEs. Our key idea is to leverage the prior of ``translational similarity'' of numerical PDE differential operators to drastically reduce the scale of learning model and training data. W...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,161
2310.17303	Demonstration-Regularized RL	Incorporating expert demonstrations has empirically helped to improve the sample efficiency of reinforcement learning (RL). This paper quantifies theoretically to what extent this extra information reduces RL's sample complexity. In particular, we study the demonstration-regularized reinforcement learning that leverage...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,078
2202.08386	Laplacian operator on statistical manifold	In this paper, we define a Laplacian operator on a statistical manifold, called the vector Laplacian. This vector Laplacian incorporates information from the Amari-Chentsov tensor. We derive a formula for the vector Laplacian. We also give two applications using the heat kernel associated with the vector Laplacian.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	280,850
2211.04086	Does an ensemble of GANs lead to better performance when training segmentation networks with synthetic images?	Large annotated datasets are required to train segmentation networks. In medical imaging, it is often difficult, time consuming and expensive to create such datasets, and it may also be difficult to share these datasets with other researchers. Different AI models can today generate very realistic synthetic images, whic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	329,132
0902.2316	On weak isometries of Preparata codes	Let C1 and C2 be codes with code distance d. Codes C1 and C2 are called weakly isometric, if there exists a mapping J:C1->C2, such that for any x,y from C1 the equality d(x,y)=d holds if and only if d(J(x),J(y))=d. Obviously two codes are weakly isometric if and only if the minimal distance graphs of these codes are is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,159
2008.06148	Complexity aspects of local minima and related notions	We consider the notions of (i) critical points, (ii) second-order points, (iii) local minima, and (iv) strict local minima for multivariate polynomials. For each type of point, and as a function of the degree of the polynomial, we study the complexity of deciding (1) if a given point is of that type, and (2) if a polyn...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	191,711
2007.00454	Pricing cyber insurance for a large-scale network	Facing the lack of cyber insurance loss data, we propose an innovative approach for pricing cyber insurance for a large-scale network based on synthetic data. The synthetic data is generated by the proposed risk spreading and recovering algorithm that allows infection and recovery events to occur sequentially, and allo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	185,123
2403.05231	Tracking Meets LoRA: Faster Training, Larger Model, Stronger Performance	Motivated by the Parameter-Efficient Fine-Tuning (PEFT) in large language models, we propose LoRAT, a method that unveils the power of large ViT model for tracking within laboratory-level resources. The essence of our work lies in adapting LoRA, a technique that fine-tunes a small subset of model parameters without add...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,926
1704.04932	Deep Relaxation: partial differential equations for optimizing deep neural networks	In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already been used successfully in this context are reinterpreted as solutions of a viscou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	71,918
2312.00025	Secure Transformer Inference Protocol	Security of model parameters and user data is critical for Transformer-based services, such as ChatGPT. While recent strides in secure two-party protocols have successfully addressed security concerns in serving Transformer models, their adoption is practically infeasible due to the prohibitive cryptographic overheads ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	411,855
2402.07340	Random Geometric Graph Alignment with Graph Neural Networks	We characterize the performance of graph neural networks for graph alignment problems in the presence of vertex feature information. More specifically, given two graphs that are independent perturbations of a single random geometric graph with noisy sparse features, the task is to recover an unknown one-to-one mapping ...	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	false	428,665
2304.07242	Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph	The pandemic of COVID-19 has inspired extensive works across different research fields. Existing literature and knowledge platforms on COVID-19 only focus on collecting papers on biology and medicine, neglecting the interdisciplinary efforts, which hurdles knowledge sharing and research collaborations between fields to...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	358,278
2106.11176	Abstract Geometrical Computation 11: Slanted Firing Squad Synchronisation on Signal Machines	Firing Squad Synchronisation on Cellular Automata is the dynamical synchronisation of finitely many cells without any prior knowledge of their range. This can be conceived as a signal with an infinite speed. Most of the proposed constructions naturally translate to the continuous setting of signal machines and generate...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	242,303
2009.04647	COVID-19 Pandemic Cyclic Lockdown Optimization Using Reinforcement Learning	This work examines the use of reinforcement learning (RL) to optimize cyclic lockdowns, which is one of the methods available for control of the COVID-19 pandemic. The problem is structured as an optimal control system for tracking a reference value, corresponding to the maximum usage level of a critical resource, such...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	195,110
2501.18229	GPD: Guided Polynomial Diffusion for Motion Planning	Diffusion-based motion planners are becoming popular due to their well-established performance improvements, stemming from sample diversity and the ease of incorporating new constraints directly during inference. However, a primary limitation of the diffusion process is the requirement for a substantial number of denoi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	528,624
2101.05209	Image Steganography based on Iteratively Adversarial Samples of A Synchronized-directions Sub-image	Nowadays a steganography has to face challenges of both feature based staganalysis and convolutional neural network (CNN) based steganalysis. In this paper, we present a novel steganography scheme denoted as ITE-SYN (based on ITEratively adversarial perturbations onto a SYNchronized-directions sub-image), by which secu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,363
2108.03601	Using Biological Variables and Social Determinants to Predict Malaria and Anemia among Children in Senegal	Integrating machine learning techniques in healthcare becomes very common nowadays, and it contributes positively to improving clinical care and health decisions planning. Anemia and malaria are two life-threatening diseases in Africa that affect the red blood cells and reduce hemoglobin production. This paper focuses ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,720
1909.01603	Multi-DoF Time Domain Passivity Approach Based Drift Compensation for Telemanipulation	When, in addition to stability, position synchronization is also desired in bilateral teleoperation, Time Domain Passivity Approach (TDPA) alone might not be able to fulfill the desired objective. This is due to an undesired effect caused by admittance type passivity controllers, namely position drift. Previous works f...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	143,954
2010.13499	Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index	In many medical imaging and classical computer vision tasks, the Dice score and Jaccard index are used to evaluate the segmentation performance. Despite the existence and great empirical success of metric-sensitive losses, i.e. relaxations of these metrics such as soft Dice, soft Jaccard and Lovasz-Softmax, many resear...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	203,154
1904.03953	Feature Learning Viewpoint of AdaBoost and a New Algorithm	The AdaBoost algorithm has the superiority of resisting overfitting. Understanding the mysteries of this phenomena is a very fascinating fundamental theoretical problem. Many studies are devoted to explaining it from statistical view and margin theory. In this paper, we illustrate it from feature learning viewpoint, an...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,892
1708.08998	Deep Structure for end-to-end inverse rendering	Inverse rendering in a 3D format denoted to recovering the 3D properties of a scene given 2D input image(s) and is typically done using 3D Morphable Model (3DMM) based methods from single view images. These models formulate each face as a weighted combination of some basis vectors extracted from the training data. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,714
1212.4906	SMML estimators for 1-dimensional continuous data	A method is given for calculating the strict minimum message length (SMML) estimator for 1-dimensional exponential families with continuous sufficient statistics. A set of $n$ equations are found that the $n$ cut-points of the SMML estimator must satisfy. These equations can be solved using Newton's method and this app...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	20,497
1906.05741	Distributed High-dimensional Regression Under a Quantile Loss Function	This paper studies distributed estimation and support recovery for high-dimensional linear regression model with heavy-tailed noise. To deal with heavy-tailed noise whose variance can be infinite, we adopt the quantile regression loss function instead of the commonly used squared loss. However, the non-smooth quantile ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	135,105
1808.00414	Variational dynamic interpolation for kinematic systems on trivial principal bundles	This article presents the dynamic interpolation problem for locomotion systems evolving on a trivial principal bundle $Q$. Given an ordered set of points in $Q$, we wish to generate a trajectory which passes through these points by synthesizing suitable controls. The global product structure of the trivial bundle is us...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	104,381
2408.13005	EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation	Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. However, relying solely on text guidance for video generation has serious limitations, as videos contain much richer content than images, espe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	482,974
1507.06833	Comparison between GFDM and VOFDM	This document provides a comparison of the transmission techniques used in Generalized Frequency Division Multiplexing (GFDM) and Vector-OFDM (VOFDM). Within the document both systems are coarsely described and common and distinct properties are highlighted.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	45,420
2409.14607	Patch Ranking: Efficient CLIP by Learning to Rank Local Patches	Contrastive image-text pre-trained models such as CLIP have shown remarkable adaptability to downstream tasks. However, they face challenges due to the high computational requirements of the Vision Transformer (ViT) backbone. Current strategies to boost ViT efficiency focus on pruning patch tokens but fall short in add...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	490,548
1507.00500	Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM	Feature selection in learning to rank has recently emerged as a crucial issue. Whereas several preprocessing approaches have been proposed, only a few works have been focused on integrating the feature selection into the learning process. In this work, we propose a general framework for feature selection in learning to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	44,764
1305.0218	Video Segmentation via Diffusion Bases	Identifying moving objects in a video sequence, which is produced by a static camera, is a fundamental and critical task in many computer-vision applications. A common approach performs background subtraction, which identifies moving objects as the portion of a video frame that differs significantly from a background m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	24,336
2103.13283	Information-based Disentangled Representation Learning for Unsupervised MR Harmonization	Accuracy and consistency are two key factors in computer-assisted magnetic resonance (MR) image analysis. However, contrast variation from site to site caused by lack of standardization in MR acquisition impedes consistent measurements. In recent years, image harmonization approaches have been proposed to compensate fo...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	226,445
2103.07281	Empirical Mode Modeling: A data-driven approach to recover and forecast nonlinear dynamics from noisy data	Data-driven, model-free analytics are natural choices for discovery and forecasting of complex, nonlinear systems. Methods that operate in the system state-space require either an explicit multidimensional state-space, or, one approximated from available observations. Since observational data are frequently sampled wit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	224,552
1805.07078	Flexible IR-HARQ Scheme for Polar-Coded Modulation	A flexible incremental redundancy hybrid auto- mated repeat request (IR-HARQ) scheme for polar codes is proposed based on dynamically frozen bits and the quasi-uniform puncturing (QUP) algorithm. The length of each transmission is not restricted to a power of two. It is applicable for the binary input additive white Ga...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	97,739
1906.10881	Automatic Hierarchical Classification of Kelps using Deep Residual Features	Across the globe, remote image data is rapidly being collected for the assessment of benthic communities from shallow to extremely deep waters on continental slopes to the abyssal seas. Exploiting this data is presently limited by the time it takes for experts to identify organisms found in these images. With this limi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,537
1908.03687	Color-Coded Fiber-Optic Tactile Sensor for an Elastomeric Robot Skin	The sense of touch is essential for reliable mapping between the environment and a robot which interacts physically with objects. Presumably, an artificial tactile skin would facilitate safe interaction of the robots with the environment. In this work, we present our color-coded tactile sensor, incorporating plastic op...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	141,296
2001.11062	Safe Predictors for Enforcing Input-Output Specifications	We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-output specifications before, during, and after algorithm training. Our method involves designing a constrained predictor for each set of compa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	161,961
2203.16377	A barrier function approach to constrained Pontryagin-based Nonlinear Model Predictive Control	A Pontryagin-based approach to solve a class of constrained Nonlinear Model Predictive Control problems is proposed which employs the method of barrier functions for dealing with the state constraints. Unlike the existing works in literature the proposed method is able to cope with nonlinear input and state constraints...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	288,766
1903.08912	PPGnet: Deep Network for Device Independent Heart Rate Estimation from Photoplethysmogram	Photoplethysmogram (PPG) is increasingly used to provide monitoring of the cardiovascular system under ambulatory conditions. Wearable devices like smartwatches use PPG to allow long term unobtrusive monitoring of heart rate in free living conditions. PPG based heart rate measurement is unfortunately highly susceptible...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,939
2407.18632	Robust VAEs via Generating Process of Noise Augmented Data	Advancing defensive mechanisms against adversarial attacks in generative models is a critical research topic in machine learning. Our study focuses on a specific type of generative models - Variational Auto-Encoders (VAEs). Contrary to common beliefs and existing literature which suggest that noise injection towards tr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	476,463
2006.11486	Unsupervised Vehicle Re-identification with Progressive Adaptation	Vehicle re-identification (reID) aims at identifying vehicles across different non-overlapping cameras views. The existing methods heavily relied on well-labeled datasets for ideal performance, which inevitably causes fateful drop due to the severe domain bias between the training domain and the real-world scenes; wors...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	183,256
2306.10270	Old and New Minimalism: a Hopf algebra comparison	In this paper we compare some old formulations of Minimalism, in particular Stabler's computational minimalism, and Chomsky's new formulation of Merge and Minimalism, from the point of view of their mathematical description in terms of Hopf algebras. We show that the newer formulation has a clear advantage purely in te...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	374,160
1509.08215	Adaptive Agent-Based SCADA System	Modern supervisory control and data acquisition (SCADA) systems comprise variety of industrial equipment such as physical control processes, logical control systems, communication networks, computers, and communication protocols. They are concerned with control and supervision of production control processes. Modern SC...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	47,342
2108.12151	A Matching Algorithm based on Image Attribute Transfer and Local Features for Underwater Acoustic and Optical Images	In the field of underwater vision research, image matching between the sonar sensors and optical cameras has always been a challenging problem. Due to the difference in the imaging mechanism between them, which are the gray value, texture, contrast, etc. of the acoustic images and the optical images are also variant in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,409
1608.02904	TweeTime: A Minimally Supervised Method for Recognizing and Normalizing Time Expressions in Twitter	We describe TweeTIME, a temporal tagger for recognizing and normalizing time expressions in Twitter. Most previous work in social media analysis has to rely on temporal resolvers that are designed for well-edited text, and therefore suffer from the reduced performance due to domain mismatch. We present a minimally supe...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	59,615
2206.14362	Lower Bounds on the Error Probability for Invariant Causal Prediction	It is common practice to collect observations of feature and response pairs from different environments. A natural question is how to identify features that have consistent prediction power across environments. The invariant causal prediction framework proposes to approach this problem through invariance, assuming a li...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	305,262
2404.01503	Some Orders Are Important: Partially Preserving Orders in Top-Quality Planning	The ability to generate multiple plans is central to using planning in real-life applications. Top-quality planners generate sets of such top-cost plans, allowing flexibility in determining equivalent ones. In terms of the order between actions in a plan, the literature only considers two extremes -- either all orders ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	443,445
2303.03986	Multiplexed gradient descent: Fast online training of modern datasets on hardware neural networks without backpropagation	We present multiplexed gradient descent (MGD), a gradient descent framework designed to easily train analog or digital neural networks in hardware. MGD utilizes zero-order optimization techniques for online training of hardware neural networks. We demonstrate its ability to train neural networks on modern machine learn...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	349,921
1110.3649	Algorithms to automatically quantify the geometric similarity of anatomical surfaces	We describe new approaches for distances between pairs of 2-dimensional surfaces (embedded in 3-dimensional space) that use local structures and global information contained in inter-structure geometric relationships. We present algorithms to automatically determine these distances as well as geometric correspondences....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	12,685
1107.4429	High Accuracy Human Activity Monitoring using Neural network	This paper presents the designing of a neural network for the classification of Human activity. A Triaxial accelerometer sensor, housed in a chest worn sensor unit, has been used for capturing the acceleration of the movements associated. All the three axis acceleration data were collected at a base station PC via a CC...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	11,399
2209.02595	A neuromorphic approach to image processing and machine vision	Neuromorphic engineering is essentially the development of artificial systems, such as electronic analog circuits that employ information representations found in biological nervous systems. Despite being faster and more accurate than the human brain, computers lag behind in recognition capability. However, it is envis...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	316,256
2108.03004	MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review	With autonomous driving developing in a booming stage, accurate object detection in complex scenarios attract wide attention to ensure the safety of autonomous driving. Millimeter wave (mmWave) radar and vision fusion is a mainstream solution for accurate obstacle detection. This article presents a detailed survey on m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,526
2312.07423	Holoported Characters: Real-time Free-viewpoint Rendering of Humans from Sparse RGB Cameras	We present the first approach to render highly realistic free-viewpoint videos of a human actor in general apparel, from sparse multi-view recording to display, in real-time at an unprecedented 4K resolution. At inference, our method only requires four camera views of the moving actor and the respective 3D skeletal pos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	414,919
2412.15983	Never Reset Again: A Mathematical Framework for Continual Inference in Recurrent Neural Networks	Recurrent Neural Networks (RNNs) are widely used for sequential processing but face fundamental limitations with continual inference due to state saturation, requiring disruptive hidden state resets. However, reset-based methods impose synchronization requirements with input boundaries and increase computational costs ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	519,328
2404.04113	BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models	Knowledge probing assesses to which degree a language model (LM) has successfully learned relational knowledge during pre-training. Probing is an inexpensive way to compare LMs of different sizes and training configurations. However, previous approaches rely on the objective function used in pre-training LMs and are th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	444,518
2303.12074	CC3D: Layout-Conditioned Generation of Compositional 3D Scenes	In this work, we introduce CC3D, a conditional generative model that synthesizes complex 3D scenes conditioned on 2D semantic scene layouts, trained using single-view images. Different from most existing 3D GANs that limit their applicability to aligned single objects, we focus on generating complex scenes with multipl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,126
2003.07596	Construe: a software solution for the explanation-based interpretation of time series	This paper presents a software implementation of a general framework for time series interpretation based on abductive reasoning. The software provides a data model and a set of algorithms to make inference to the best explanation of a time series, resulting in a description in multiple abstraction levels of the proces...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	168,482
2308.05123	Towards Automatic Scoring of Spinal X-ray for Ankylosing Spondylitis	Manually grading structural changes with the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS) on spinal X-ray imaging is costly and time-consuming due to bone shape complexity and image quality variations. In this study, we address this challenge by prototyping a 2-step auto-grading pipeline, called VertXGra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	384,691
2407.19164	Addressing Topic Leakage in Cross-Topic Evaluation for Authorship Verification	Authorship verification (AV) aims to identify whether a pair of texts has the same author. We address the challenge of evaluating AV models' robustness against topic shifts. The conventional evaluation assumes minimal topic overlap between training and test data. However, we argue that there can still be topic leakage ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	476,669
2410.18270	Multilingual Hallucination Gaps in Large Language Models	Large language models (LLMs) are increasingly used as alternatives to traditional search engines given their capacity to generate text that resembles human language. However, this shift is concerning, as LLMs often generate hallucinations, misleading or false information that appears highly credible. In this study, we ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	501,817
2311.01813	FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation	Recently, open-domain text-to-video (T2V) generation models have made remarkable progress. However, the promising results are mainly shown by the qualitative cases of generated videos, while the quantitative evaluation of T2V models still faces two critical problems. Firstly, existing studies lack fine-grained evaluati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	405,187
2201.09457	Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity	We propose a new policy gradient method, named homotopic policy mirror descent (HPMD), for solving discounted, infinite horizon MDPs with finite state and action spaces. HPMD performs a mirror descent type policy update with an additional diminishing regularization term, and possesses several computational properties t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	276,682
1904.09374	Two-Timescale Voltage Control in Distribution Grids Using Deep Reinforcement Learning	Modern distribution grids are currently being challenged by frequent and sizable voltage fluctuations, due mainly to the increasing deployment of electric vehicles and renewable generators. Existing approaches to maintaining bus voltage magnitudes within the desired region can cope with either traditional utility-owned...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	128,357
2110.14013	Deep Integrated Pipeline of Segmentation Guided Classification of Breast Cancer from Ultrasound Images	Breast cancer has become a symbol of tremendous concern in the modern world, as it is one of the major causes of cancer mortality worldwide. In this regard, breast ultrasonography images are frequently utilized by doctors to diagnose breast cancer at an early stage. However, the complex artifacts and heavily noised bre...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	263,380
2004.06091	Selective Encoding Policies for Maximizing Information Freshness	An information source generates independent and identically distributed status update messages from an observed random phenomenon which takes $n$ distinct values based on a given pmf. These update packets are encoded at the transmitter node to be sent to a receiver node which wants to track the observed random variable...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	172,413
1904.05216	Dungeons for Science: Mapping Belief Places and Spaces	Tabletop fantasy role-playing games (TFRPGs) have existed in offline and online contexts for many decades, yet are rarely featured in scientific literature. This paper presents a case study where TFRPGs were used to generate and collect data for maps of belief environments using fiction co-created by multiple small gro...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	127,240
2501.18592	Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models	In real-world scenarios, achieving domain adaptation and generalization poses significant challenges, as models must adapt to or generalize across unknown target distributions. Extending these capabilities to unseen multimodal distributions, i.e., multimodal domain adaptation and generalization, is even more challengin...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	528,767
2008.06957	Improving Services Offered by Internet Providers by Analyzing Online Reviews using Text Analytics	With the proliferation of digital infrastructure, there is a plethora of demand for internet services, which makes the wireless communications industry highly competitive. Thus internet service providers (ISPs) must ensure that their efforts are targeted towards attracting and retaining customers to ensure continued gr...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	191,945
2403.17011	SUDO: a framework for evaluating clinical artificial intelligence systems without ground-truth annotations	A clinical artificial intelligence (AI) system is often validated on a held-out set of data which it has not been exposed to before (e.g., data from a different hospital with a distinct electronic health record system). This evaluation process is meant to mimic the deployment of an AI system on data in the wild; those ...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	441,289
2403.11211	RCdpia: A Renal Carcinoma Digital Pathology Image Annotation dataset based on pathologists	The annotation of digital pathological slide data for renal cell carcinoma is of paramount importance for correct diagnosis of artificial intelligence models due to the heterogeneous nature of the tumor. This process not only facilitates a deeper understanding of renal cell cancer heterogeneity but also aims to minimiz...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,596
2204.04980	A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition	Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued pre-training on task-specific out-of-domain data or fine-tuning on in-domain data. However, their performance in low-resource scenarios, where such data is not available, remain...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	290,869
2002.07246	Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness	Recently smoothing deep neural network based classifiers via isotropic Gaussian perturbation is shown to be an effective and scalable way to provide state-of-the-art probabilistic robustness guarantee against $\ell_2$ norm bounded adversarial perturbations. However, how to train a good base classifier that is accurate ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,411
1801.08099	Logically-Constrained Reinforcement Learning	We present the first model-free Reinforcement Learning (RL) algorithm to synthesise policies for an unknown Markov Decision Process (MDP), such that a linear time property is satisfied. The given temporal property is converted into a Limit Deterministic Buchi Automaton (LDBA) and a robust reward function is defined ove...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	88,898
2210.11475	On the economic viability of solar energy when upgrading cellular networks	The massive increase of data traffic, the widespread proliferation of wireless applications and the full-scale deployment of 5G and the IoT, imply a steep increase in cellular networks energy use, resulting in a significant carbon footprint. This paper presents a comprehensive model to show the interaction between the ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	325,328
2311.05006	Familiarity-Based Open-Set Recognition Under Adversarial Attacks	Open-set recognition (OSR), the identification of novel categories, can be a critical component when deploying classification models in real-world applications. Recent work has shown that familiarity-based scoring rules such as the Maximum Softmax Probability (MSP) or the Maximum Logit Score (MLS) are strong baselines ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	406,433
2102.08818	SciDr at SDU-2020: IDEAS -- Identifying and Disambiguating Everyday Acronyms for Scientific Domain	We present our systems submitted for the shared tasks of Acronym Identification (AI) and Acronym Disambiguation (AD) held under Workshop on SDU. We mainly experiment with BERT and SciBERT. In addition, we assess the effectiveness of "BIOless" tagging and blending along with the prowess of ensembling in AI. For AD, we f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	220,581
2312.14525	An Approach to Reduce Computational Load: Precalculating Gain Matrices for an LQR Controller of a Four-Axis Manipulator Using State Space Kinematics	When designing a power or CPU constrained device where a four-axis robotic arm is required and access to the Robot Operating System (ROS) is not an option, finding an efficient state space controller for a four-axis arm can be an obstacle. In this paper, I explore a method to optimize the computing power required for a...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	417,669
1911.10119	GANkyoku: a Generative Adversarial Network for Shakuhachi Music	A common approach to generating symbolic music using neural networks involves repeated sampling of an autoregressive model until the full output sequence is obtained. While such approaches have shown some promise in generating short sequences of music, this typically has not extended to cases where the final target seq...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	154,736
1912.01553	Learning Spatially Structured Image Transformations Using Planar Neural Networks	Learning image transformations is essential to the idea of mental simulation as a method of cognitive inference. We take a connectionist modeling approach, using planar neural networks to learn fundamental imagery transformations, like translation, rotation, and scaling, from perceptual experiences in the form of image...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	156,118
2306.02679	Joint Pre-training and Local Re-training: Transferable Representation Learning on Multi-source Knowledge Graphs	In this paper, we present the ``joint pre-training and local re-training'' framework for learning and applying multi-source knowledge graph (KG) embeddings. We are motivated by the fact that different KGs contain complementary information to improve KG embeddings and downstream tasks. We pre-train a large teacher KG em...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	371,007
2412.04649	Generating Whole-Body Avoidance Motion through Localized Proximity Sensing	This paper presents a novel control algorithm for robotic manipulators in unstructured environments using proximity sensors partially distributed on the platform. The proposed approach exploits arrays of multi zone Time-of-Flight (ToF) sensors to generate a sparse point cloud representation of the robot surroundings. B...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	514,497
2103.07248	Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks	The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems. Increasing shares of distributed energy resources (e.g. renewable energy generators, electric vehicles) and internet-connected sensing and control devices (e.g. smart heating and cooling)...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	224,540
2308.10120	Deep Generative Modeling-based Data Augmentation with Demonstration using the BFBT Benchmark Void Fraction Datasets	Deep learning (DL) has achieved remarkable successes in many disciplines such as computer vision and natural language processing due to the availability of ``big data''. However, such success cannot be easily replicated in many nuclear engineering problems because of the limited amount of training data, especially when...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	386,582
1910.12388	A memory enhanced LSTM for modeling complex temporal dependencies	In this paper, we present Gamma-LSTM, an enhanced long short term memory (LSTM) unit, to enable learning of hierarchical representations through multiple stages of temporal abstractions. Gamma memory, a hierarchical memory unit, forms the central memory of Gamma-LSTM with gates to regulate the information flow into var...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,074
2203.02833	Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference	Multiparty computation approaches to secure neural network inference commonly rely on garbled circuits for securely executing nonlinear activation functions. However, garbled circuits require excessive communication between server and client, impose significant storage overheads, and incur large runtime penalties. To r...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	283,878
1601.05650	Exponent Function for Source Coding with Side Information at the Decoder at Rates below the Rate Distortion Function	We consider the rate distortion problem with side information at the decoder posed and investigated by Wyner and Ziv. The rate distortion function indicating the trade-off between the rate on the data compression and the quality of data obtained at the decoder was determined by Wyner and Ziv. In this paper, we study th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,150
2102.09600	Within-Document Event Coreference with BERT-Based Contextualized Representations	Event coreference continues to be a challenging problem in information extraction. With the absence of any external knowledge bases for events, coreference becomes a clustering task that relies on effective representations of the context in which event mentions appear. Recent advances in contextualized language represe...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	220,826
2002.09849	Multi-Antenna UAV Data Harvesting: Joint Trajectory and Communication Optimization	Unmanned aerial vehicle (UAV)-enabled communication is a promising technology to extend coverage and enhance throughput for traditional terrestrial wireless communication systems. In this paper, we consider a UAV-enabled wireless sensor network (WSN), where a multi-antenna UAV is dispatched to collect data from a group...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	165,205
2303.08046	Ultra-High-Resolution Detector Simulation with Intra-Event Aware GAN and Self-Supervised Relational Reasoning	Simulating high-resolution detector responses is a computationally intensive process that has long been challenging in Particle Physics. Despite the ability of generative models to streamline it, full ultra-high-granularity detector simulation still proves to be difficult as it contains correlated and fine-grained info...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	351,487
2411.09020	Predictive Visuo-Tactile Interactive Perception Framework for Object Properties Inference	Interactive exploration of the unknown physical properties of objects such as stiffness, mass, center of mass, friction coefficient, and shape is crucial for autonomous robotic systems operating continuously in unstructured environments. Precise identification of these properties is essential to manipulate objects in a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	508,102
2202.03173	Towards Loosely-Coupling Knowledge Graph Embeddings and Ontology-based Reasoning	Knowledge graph completion (a.k.a.~link prediction), i.e.,~the task of inferring missing information from knowledge graphs, is a widely used task in many applications, such as product recommendation and question answering. The state-of-the-art approaches of knowledge graph embeddings and/or rule mining and reasoning ar...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	279,103
2403.12432	Prototipo de video juego activo basado en una c\'amara 3D para motivar la actividad f\'isica en ni\~nos y adultos mayores	This document describes the development of a video game prototype designed to encourage physical activity among children and older adults. The prototype consists of a laptop, a camera with 3D sensors, and optionally requires an LCD screen or a projector. The programming component of this prototype was developed in Scra...	true	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	439,179
1706.01330	Neuroevolution on the Edge of Chaos	Echo state networks represent a special type of recurrent neural networks. Recent papers stated that the echo state networks maximize their computational performance on the transition between order and chaos, the so-called edge of chaos. This work confirms this statement in a comprehensive set of experiments. Furthermo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	74,783
2305.10055	Optimized Joint Beamforming for Wireless Powered Over-the-Air Computation	This correspondence studies the wireless powered over-the-air computation (AirComp) for achieving sustainable wireless data aggregation (WDA) by integrating AirComp and wireless power transfer (WPT) into a joint design. In particular, we consider that a multi-antenna hybrid access point (HAP) employs the transmit energ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	364,890
2106.14623	Polyconvex anisotropic hyperelasticity with neural networks	In the present work, two machine learning based constitutive models for finite deformations are proposed. Using input convex neural networks, the models are hyperelastic, anisotropic and fulfill the polyconvexity condition, which implies ellipticity and thus ensures material stability. The first constitutive model is b...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	243,470

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