Papers
Enhancing Sufficient Dimension Reduction via Hellinger Correlation
Seungbeom Hong, Ilmun Kim, Jun Song
Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
Pranav Singh Chib, Pravendra Singh
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning
Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li et al.
Enhancing Vision Transformer: Amplifying Non-Linearity in Feedforward Network Module
Yixing Xu, Chao Li, Dong Li et al.
Ensemble Pruning for Out-of-distribution Generalization
Fengchun Qiao, Xi Peng
Entropy-Reinforced Planning with Large Language Models for Drug Discovery
Xuefeng Liu, Chih-Chan Tien, Peng Ding et al.
Environment Design for Inverse Reinforcement Learning
Thomas Kleine Buening, Victor Villin, Christos Dimitrakakis
Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection
Chentao Cao, Zhun Zhong, Zhanke Zhou et al.
EquiAV: Leveraging Equivariance for Audio-Visual Contrastive Learning
Jongsuk Kim, Hyeongkeun Lee, Kyeongha Rho et al.
Equilibrium of Data Markets with Externality
Safwan Hossain, Yiling Chen
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
Yang Zhang, Zhewei Wei, Ye Yuan et al.
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
Yuchao Lin, Jacob Helwig, Shurui Gui et al.
Equivariant Deep Weight Space Alignment
Aviv Navon, Aviv Shamsian, Ethan Fetaya et al.
Equivariant Diffusion for Crystal Structure Prediction
Peijia Lin, Pin Chen, Rui Jiao et al.
Equivariant Frames and the Impossibility of Continuous Canonicalization
Nadav Dym, Hannah Lawrence, Jonathan W. Siegel
Equivariant Graph Neural Operator for Modeling 3D Dynamics
Minkai Xu, Jiaqi Han, Aaron Lou et al.
ERQ: Error Reduction for Post-Training Quantization of Vision Transformers
Yunshan Zhong, Jiawei Hu, You Huang et al.
Error Feedback Can Accurately Compress Preconditioners
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic et al.
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling
Kangjie Zheng, Siyu Long, Tianyu Lu et al.
ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection
Hongyu Liu, Runmin Cong, Hua Li et al.
Estimating Barycenters of Distributions with Neural Optimal Transport
Alexander Kolesov, Petr Mokrov, Igor Udovichenko et al.
Estimating Canopy Height at Scale
Jan Pauls, Max Zimmer, Una M. Kelly et al.
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
Estimating the Permanent by Nesting Importance Sampling
Juha Harviainen, Mikko Koivisto