csquires / causal-rep-learning-reading-group
☆21Updated last year
Related projects ⓘ
Alternatives and complementary repositories for causal-rep-learning-reading-group
- ☆43Updated 2 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆42Updated 4 years ago
- TensorFlow implementation of 'Core', proposed in "Conditional Variance Penalties and Domain Shift Robustness".☆10Updated 6 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆92Updated 2 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆80Updated 7 months ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆15Updated 4 years ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆72Updated 2 years ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆54Updated 8 months ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆68Updated 3 years ago
- ☆33Updated 5 years ago
- ☆18Updated 11 months ago
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆46Updated 8 months ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆27Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 2 years ago
- ☆30Updated 6 years ago
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 5 years ago
- Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning☆48Updated 3 years ago
- ☆37Updated 5 years ago
- ☆42Updated 6 years ago
- Deconfounding Reinforcement Learning in Observational Settings☆48Updated 5 years ago
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated 4 months ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆19Updated last year
- Natural Gradient, Variational Inference☆29Updated 4 years ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 3 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago