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Showing 76–100 of 226 papers

TitleStatusHype
Boosting Offline Reinforcement Learning via Data Rebalancing—0
Addressing Distribution Shift in Online Reinforcement Learning with Offline Datasets—0
Deep autoregressive density nets vs neural ensembles for model-based offline reinforcement learning—0
Analytic Energy-Guided Policy Optimization for Offline Reinforcement Learning—0
Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network—0
Decision SpikeFormer: Spike-Driven Transformer for Decision Making—0
Align Your Intents: Offline Imitation Learning via Optimal Transport—0
Decision Mamba: Reinforcement Learning via Hybrid Selective Sequence Modeling—0
DCE: Offline Reinforcement Learning With Double Conservative Estimates—0
Improving Behavioural Cloning with Positive Unlabeled Learning—0
Accelerating Residual Reinforcement Learning with Uncertainty Estimation—0
HIPODE: Enhancing Offline Reinforcement Learning with High-Quality Synthetic Data from a Policy-Decoupled Approach—0
Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning—0
Guided Data Augmentation for Offline Reinforcement Learning and Imitation Learning—0
Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics—0
Learning Computational Efficient Bots with Costly Features—0
Learning from Random Demonstrations: Offline Reinforcement Learning with Importance-Sampled Diffusion Models—0
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning—0
Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL—0
From Novelty to Imitation: Self-Distilled Rewards for Offline Reinforcement Learning—0
Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning—0
A Behavior Regularized Implicit Policy for Offline Reinforcement Learning—0
Hierarchical Decision Transformer—0
Forward KL Regularized Preference Optimization for Aligning Diffusion Policies—0
Flow to Control: Offline Reinforcement Learning with Lossless Primitive Discovery—0
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