[NeurIPS2021] Federated Reinforcement Learning with Theoretical Guarantees. The repo contains code and experiments for our Federated Policy Gradient with Byzantine Resilience framework for improving sample efficiency of RL agents.
A paper list of sample-efficient reinforcement learning
This repository contains code associated with SHIRE: Enhancing Sample Efficiency using Human Intuition in Reinforcement Learning (ICRA 2025)
Implementation of our IJCAI 2022 paper "CCLF: A Contrastive-Curiosity-Driven Learning Framework for Sample-Efficient Reinforcement Learning".
Collection of codes pertaining to my research in model-free RL algorithms.
[RLC2025] - Official repository of "SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Reinforcement Learning"
[NeurIPS 2023] CycAug implementation from paper 'Learning Better with Less: Effective Augmentation for Sample-Efficient Visual RL'.
Bachelor Thesis: Sample-Efficient Bayesian Model-Based Reinforcement Learning Using DBN and PPL Models
PyTorch implementation (with up-to-date tooling) of the SAM / DAC algorithm
Reinforcement learning framework for environments with action-order invariance to achieve sample efficiency gains
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