Papers
Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network
Yadi Cao, Menglei Chai, Minchen Li et al.
Efficient List-Decodable Regression using Batches
Abhimanyu Das, Ayush Jain, Weihao Kong et al.
Efficiently predicting high resolution mass spectra with graph neural networks
Michael Murphy, Stefanie Jegelka, Ernest Fraenkel et al.
Efficient Online Reinforcement Learning with Offline Data
Philip J. Ball, Laura Smith, Ilya Kostrikov et al.
Efficient Parametric Approximations of Neural Network Function Space Distance
Nikita Dhawan, Sicong Huang, Juhan Bae et al.
Efficient Personalized Federated Learning via Sparse Model-Adaptation
Daoyuan Chen, Liuyi Yao, Dawei Gao et al.
Efficient preconditioned stochastic gradient descent for estimation in latent variable models
Charlotte Baey, Maud Delattre, Estelle Kuhn et al.
Efficient Quantum Algorithms for Quantum Optimal Control
Xiantao Li, Chunhao Wang
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation
Orin Levy, Alon Cohen, Asaf Cassel et al.
Efficient RL via Disentangled Environment and Agent Representations
Kevin Gmelin, Shikhar Bahl, Russell Mendonca et al.
Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language
Alexei Baevski, Arun Babu, Wei-Ning Hsu et al.
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
Hainan Xu, Fei Jia, Somshubra Majumdar et al.
Efficient Training of Language Models using Few-Shot Learning
Sashank J. Reddi, Sobhan Miryoosefi, Stefani Karp et al.
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification
Juan Maroñas, Daniel Hernández-Lobato
Eliminating Adversarial Noise via Information Discard and Robust Representation Restoration
Dawei Zhou, Yukun Chen, Nannan Wang et al.
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models
Qinglong Tian, Xin Zhang, Jiwei Zhao
Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning
Aqeel Labash, Florian Stelzer, Daniel Majoral et al.
Emergence of Sparse Representations from Noise
Trenton Bricken, Rylan Schaeffer, Bruno Olshausen et al.
Emergent Agentic Transformer from Chain of Hindsight Experience
Hao Liu, Pieter Abbeel
Emergent Asymmetry of Precision and Recall for Measuring Fidelity and Diversity of Generative Models in High Dimensions
Mahyar Khayatkhoei, Wael Abdalmageed
EM-Network: Oracle Guided Self-distillation for Sequence Learning
Ji Won Yoon, Sunghwan Ahn, Hyeonseung Lee et al.
Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets
Nils Kohring, Fabian Raoul Pieroth, Martin Bichler
End-to-end Differentiable Clustering with Associative Memories
Bishwajit Saha, Dmitry Krotov, Mohammed J Zaki et al.
End-to-End Full-Atom Antibody Design
Xiangzhe Kong, Wenbing Huang, Yang Liu
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
Yves Rychener, Daniel Kuhn, Tobias Sutter