:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Lau, Elaine, Lu, Stephen Zhewen, Pan, Ling, Precup, Doina, Bengio, Emmanuel
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2402.05234
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Discrete Probabilistic Inference as Control in Multi-path Environments
by: Deleu, Tristan, et al.
Published: (2024)

Relative Trajectory Balance is equivalent to Trust-PCL
by: Deleu, Tristan, et al.
Published: (2025)

A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings
by: Alver, Safa, et al.
Published: (2022)

Adaptive Exploration for Data-Efficient General Value Function Evaluations
by: Jain, Arushi, et al.
Published: (2024)

Functional Acceleration for Policy Mirror Descent
by: Chelu, Veronica, et al.
Published: (2024)

Diversity-Enriched Option-Critic
by: Kamat, Anand, et al.
Published: (2020)

Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
by: Zhao, Mingde, et al.
Published: (2023)

Balancing Plasticity and Stability with Fast and Slow Successor Features
by: Chua, Raymond, et al.
Published: (2026)

On the Privacy of Selection Mechanisms with Gaussian Noise
by: Lebensold, Jonathan, et al.
Published: (2024)

Conditions on Preference Relations that Guarantee the Existence of Optimal Policies
by: Carr, Jonathan Colaço, et al.
Published: (2023)

Partial Models for Building Adaptive Model-Based Reinforcement Learning Agents
by: Alver, Safa, et al.
Published: (2024)

Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
by: Arnob, Samin Yeasar, et al.
Published: (2025)

Random Policy Evaluation Uncovers Policies of Generative Flow Networks
by: He, Haoran, et al.
Published: (2024)

Fluid-Agent Reinforcement Learning
by: Sharma, Shishir, et al.
Published: (2026)

Parseval Regularization for Continual Reinforcement Learning
by: Chung, Wesley, et al.
Published: (2024)

Langevin Soft Actor-Critic: Efficient Exploration through Uncertainty-Driven Critic Learning
by: Ishfaq, Haque, et al.
Published: (2025)

Structure Language Models for Protein Conformation Generation
by: Lu, Jiarui, et al.
Published: (2024)

Cell Morphology-Guided Small Molecule Generation with GFlowNets
by: Lu, Stephen Zhewen, et al.
Published: (2024)

Incorporating Spatial Information into Goal-Conditioned Hierarchical Reinforcement Learning via Graph Representations
by: Zhang, Shuyuan, et al.
Published: (2025)

Finite time analysis of temporal difference learning with linear function approximation: Tail averaging and regularisation
by: Patil, Gandharv, et al.
Published: (2022)

Learning Successor Features the Simple Way
by: Chua, Raymond, et al.
Published: (2024)

Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
by: Carr, Jonathan Colaço, et al.
Published: (2026)

Provable and Practical: Efficient Exploration in Reinforcement Learning via Langevin Monte Carlo
by: Ishfaq, Haque, et al.
Published: (2023)

Rotation-Preserving Supervised Fine-Tuning
by: Jin, Hangzhan, et al.
Published: (2026)

Capacity-Constrained Continual Learning
by: Wen, Zheng, et al.
Published: (2025)

Fairness in Reinforcement Learning with Bisimulation Metrics
by: Rezaei-Shoshtari, Sahand, et al.
Published: (2024)

Policy Gradient Methods in the Presence of Symmetries and State Abstractions
by: Panangaden, Prakash, et al.
Published: (2023)

Understanding Behavioral Metric Learning: A Large-Scale Study on Distracting Reinforcement Learning Environments
by: Luo, Ziyan, et al.
Published: (2025)

More Efficient Randomized Exploration for Reinforcement Learning via Approximate Sampling
by: Ishfaq, Haque, et al.
Published: (2024)

Baking Symmetry into GFlowNets
by: Ma, George, et al.
Published: (2024)

Investigating Generalization Behaviours of Generative Flow Networks
by: Atanackovic, Lazar, et al.
Published: (2024)

Learning to Scale Logits for Temperature-Conditional GFlowNets
by: Kim, Minsu, et al.
Published: (2023)

Code as Reward: Empowering Reinforcement Learning with VLMs
by: Venuto, David, et al.
Published: (2024)

Action abstractions for amortized sampling
by: Boussif, Oussama, et al.
Published: (2024)

Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
by: McCracken, Gavin, et al.
Published: (2025)

Effective Protein-Protein Interaction Exploration with PPIretrieval
by: Hua, Chenqing, et al.
Published: (2024)

Mitigating Downstream Model Risks via Model Provenance
by: Wang, Keyu, et al.
Published: (2024)

MUDiff: Unified Diffusion for Complete Molecule Generation
by: Hua, Chenqing, et al.
Published: (2023)

Offline Multitask Representation Learning for Reinforcement Learning
by: Ishfaq, Haque, et al.
Published: (2024)

Detoxifying LLMs via Representation Erasure-Based Preference Optimization
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2026)