ZhaozhiQIAN / Compartmental-GP-NeurIPS-2020
Source code for "When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes" (NeurIPS 2020)
☆10Updated 3 years ago
Alternatives and similar repositories for Compartmental-GP-NeurIPS-2020:
Users that are interested in Compartmental-GP-NeurIPS-2020 are comparing it to the libraries listed below
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆34Updated 2 years ago
- Deconfounding Reinforcement Learning in Observational Settings☆48Updated 5 years ago
- Official implementation of Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning at ICML…☆37Updated 3 years ago
- ☆13Updated 5 years ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated last year
- Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning☆48Updated 3 years ago
- Code for paper Causal Confusion in Imitation Learning☆44Updated 5 years ago
- ☆31Updated 2 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆42Updated 4 years ago
- ☆77Updated 3 years ago
- ☆43Updated 2 years ago
- Code and data for the paper "Understanding Hidden Context in Preference Learning: Consequences for RLHF"☆28Updated last year
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆17Updated 2 years ago
- Implementation codes and datasets used in ICLR'22 Spotlight paper AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning…☆36Updated 9 months ago
- Representation Learning in RL☆16Updated 2 years ago
- ☆24Updated 3 years ago
- Code for "Causal autoregressive flows" - AISTATS, 2021☆44Updated 3 years ago
- Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)☆13Updated 6 years ago
- Source code for NeurIPS 2019 paper "Learning Latent Processes from High-Dimensional Event Sequences via Efficient Sampling""☆10Updated 3 years ago
- ☆32Updated 6 years ago
- learning point processes by means of optimal transport and wasserstein distance☆54Updated 6 years ago
- ☆47Updated 2 years ago
- Scalable Bayesian Inverse Reinforcement Learning (ICLR 2021) by Alex J. Chan and Mihaela van der Schaar.☆44Updated 3 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 2 years ago
- PyTorch implementation of "Model-based Reinforcement Learning for Semi-Markov Decision Processes with Neural ODEs", NeurIPS 2020☆39Updated 4 years ago
- ☆22Updated last year
- Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.☆58Updated 3 years ago
- ☆33Updated 5 years ago
- Library for Auto-Encoding Sequential Monte Carlo☆18Updated 11 months ago