Papers
11,951 papers found
Environment Predictive Coding for Visual Navigation
Santhosh Kumar Ramakrishnan, Tushar Nagarajan, Ziad Al-Halah et al.
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
Haorui Wang, Haoteng Yin, Muhan Zhang et al.
Equivariant Graph Mechanics Networks with Constraints
Wenbing Huang, Jiaqi Han, Yu Rong et al.
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
Rumen Dangovski, Li Jing, Charlotte Loh et al.
Equivariant Subgraph Aggregation Networks
Beatrice Bevilacqua, Fabrizio Frasca, Derek Lim et al.
Equivariant Transformers for Neural Network based Molecular Potentials
Philipp Thölke, Gianni De Fabritiis
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems
Thomas Pethick, Puya Latafat, Panos Patrinos et al.
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent
Oliver Bryniarski, Nabeel Hingun, Pedro Pachuca et al.
Evaluating Disentanglement of Structured Representations
Raphaël Dang-Nhu
Evaluating Distributional Distortion in Neural Language Modeling
Benjamin LeBrun, Alessandro Sordoni, Timothy J. O'Donnell
Evaluating Model-Based Planning and Planner Amortization for Continuous Control
Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim et al.
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
Leslie O'Bray, Max Horn, Bastian Rieck et al.
Evidential Turing Processes
Melih Kandemir, Abdullah Akgül, Manuel Haussmann et al.
EViT: Expediting Vision Transformers via Token Reorganizations
Youwei Liang, Chongjian GE, Zhan Tong et al.
Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning
Yutong Wang, Ke Xue, Chao Qian
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
Zirui Liu, Kaixiong Zhou, Fan Yang et al.
Explainable GNN-Based Models over Knowledge Graphs
David Jaime Tena Cucala, Bernardo Cuenca Grau, Egor V. Kostylev et al.
Explaining Point Processes by Learning Interpretable Temporal Logic Rules
Shuang Li, Mingquan Feng, Lu Wang et al.
Explanations of Black-Box Models based on Directional Feature Interactions
Aria Masoomi, Davin Hill, Zhonghui Xu et al.
Exploiting Class Activation Value for Partial-Label Learning
Fei Zhang, Lei Feng, Bo Han et al.
Exploring extreme parameter compression for pre-trained language models
Benyou Wang, Yuxin Ren, Lifeng Shang et al.
Exploring Memorization in Adversarial Training
Yinpeng Dong, Ke Xu, Xiao Yang et al.
Exploring the Limits of Large Scale Pre-training
Samira Abnar, Mostafa Dehghani, Behnam Neyshabur et al.
Exposing the Implicit Energy Networks behind Masked Language Models via Metropolis--Hastings
Kartik Goyal, Chris Dyer, Taylor Berg-Kirkpatrick
Expressiveness and Approximation Properties of Graph Neural Networks
Floris Geerts, Juan L Reutter