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Unreal environments for reinforcement learning
Collection of papers and resources for data augmentation (DA) in visual reinforcement learning (RL).
Official PyTorch implementation of "Entity-Centric Reinforcement Learning for Object Manipulation from Pixels", Haramati et al., ICLR 2024
Official pytorch implementation of the paper [Environment Agnostic Representation for Visual Reinforcement learning]
Implementation of the DQN and DRQN algorithms in Keras and tensorflow
[ICLR 2024] Adaptive Replay Ratio implementation from 'Revisiting Plasticity in Visual RL: Data, Modules and Training Stages'.
[NeurIPS 2023] CycAug implementation from paper 'Learning Better with Less: Effective Augmentation for Sample-Efficient Visual RL'.
The official implementation of the ECCV 2024 paper "Empowering Embodied Visual Tracking with Visual Foundation Models and Offline RL"