Papers
11,015 papers found
QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu et al.
Quantifying Differences in Reward Functions
Adam Gleave, Michael D Dennis, Shane Legg et al.
Random Feature Attention
Hao Peng, Nikolaos Pappas, Dani Yogatama et al.
Randomized Automatic Differentiation
Deniz Oktay, Nick McGreivy, Joshua Aduol et al.
Randomized Ensembled Double Q-Learning: Learning Fast Without a Model
Xinyue Chen, Che Wang, Zijian Zhou et al.
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments
Daochen Zha, Wenye Ma, Lei Yuan et al.
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator
Max B Paulus, Chris J. Maddison, Andreas Krause
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets
Hayeon Lee, Eunyoung Hyung, Sung Ju Hwang
Rapid Task-Solving in Novel Environments
Samuel Ritter, Ryan Faulkner, Laurent Sartran et al.
Recurrent Independent Mechanisms
Anirudh Goyal, Alex Lamb, Jordan Hoffmann et al.
Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks
Thomas Bird, Friso Kingma, David Barber
Refining Deep Generative Models via Discriminator Gradient Flow
Abdul Fatir Ansari, Ming Liang Ang, Harold Soh
Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control
Zhuang Liu, Xuanlin Li, Bingyi Kang et al.
Regularized Inverse Reinforcement Learning
Wonseok Jeon, Chen-Yang Su, Paul Barde et al.
Reinforcement Learning with Random Delays
Yann Bouteiller, Simon Ramstedt, Giovanni Beltrame et al.
Relating by Contrasting: A Data-efficient Framework for Multimodal Generative Models
Yuge Shi, Brooks Paige, Philip Torr et al.
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul et al.
Removing Undesirable Feature Contributions Using Out-of-Distribution Data
Saehyung Lee, Changhwa Park, Hyungyu Lee et al.
Representation Balancing Offline Model-based Reinforcement Learning
Byung-Jun Lee, Jongmin Lee, Kee-Eung Kim
Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
Garrett Honke, Irina Higgins, Nina Thigpen et al.
Representation Learning for Sequence Data with Deep Autoencoding Predictive Components
Junwen Bai, Weiran Wang, Yingbo Zhou et al.
Representation Learning via Invariant Causal Mechanisms
Jovana Mitrovic, Brian McWilliams, Jacob C Walker et al.
Representing Partial Programs with Blended Abstract Semantics
Maxwell Nye, Yewen Pu, Matthew Bowers et al.
Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
Namyeong Kwon, Hwidong Na, Gabriel Huang et al.
Reset-Free Lifelong Learning with Skill-Space Planning
Kevin Lu, Aditya Grover, Pieter Abbeel et al.