ioanabica / Invariant-Causal-Imitation-Learning
Code for NeurIPS 2021 paper: "Invariant Causal Imitation Learning for Generalizable Policies" by I. Bica, D. Jarrett, M. van der Schaar
☆27Updated 3 years ago
Alternatives and similar repositories for Invariant-Causal-Imitation-Learning:
Users that are interested in Invariant-Causal-Imitation-Learning are comparing it to the libraries listed below
- ☆43Updated 2 years ago
- Official implementation of Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning at ICML…☆38Updated 3 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆42Updated 4 years ago
- Deconfounding Reinforcement Learning in Observational Settings☆50Updated 5 years ago
- Implementation codes and datasets used in ICLR'22 Spotlight paper AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning…☆36Updated 11 months ago
- Scalable Bayesian Inverse Reinforcement Learning (ICLR 2021) by Alex J. Chan and Mihaela van der Schaar.☆45Updated 4 years ago
- ☆32Updated 6 years ago
- ☆37Updated 6 years ago
- Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning☆48Updated 3 years ago
- Code for the paper: "Causal Influence Detection for Improving Efficiency in Reinforcement Learning", by Seitzer, M., Schölkopf, B., Marti…☆38Updated 3 years ago
- [TNNLS-2024, arXiv-2023.2.10] Official repository of "A Survey on Causal Reinforcement Learning"☆18Updated 2 weeks ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated 2 years ago
- ☆17Updated 5 years ago
- Implementation of "Reinforcement Learning in Possibly Nonstationary Environments"☆9Updated 2 weeks ago
- A curated list of causal reinforcement learning resources.☆78Updated last year
- Public code for implementation and experiments with differentiable decision trees.☆24Updated 5 months ago
- Official Implementation of the paper "Variational Causal Networks: Approximate Bayesian Inference over Causal Structures"