andrewk1 / pytorch-deep-bayesian-bandits
PyTorch port and extension of the Deep Bayesian Bandits Library
☆42Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for pytorch-deep-bayesian-bandits
- Code for "Neural causal learning from unknown interventions"☆99Updated 4 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Simple tools for statistical analyses in RL experiments☆66Updated 6 years ago
- Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"☆39Updated 6 years ago
- Code for "Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models" (ICML 2019)☆42Updated 4 years ago
- Invariant Causal Prediction for Block MDPs☆43Updated 4 years ago
- Code for "Recurrent Independent Mechanisms"☆118Updated 2 years ago
- Code for "Systematic Generalization: What Is Required and Can It Be Learned"☆37Updated 5 years ago
- Code for "Stochastic Optimization of Sorting Networks using Continuous Relaxations", ICLR 2019.☆134Updated last year
- Implementation of Model-Agnostic Meta-Learning (MAML) in Jax☆188Updated 2 years ago
- Adapting the AlphaZero algorithm to remove the need of execution traces to train NPI.☆78Updated last year
- Code accompanying the OptionGAN paper.☆43Updated 6 years ago
- ☆13Updated 5 years ago
- ☆158Updated 3 months ago
- ☆85Updated 3 months ago
- This repository contains code for the method and experiments of the paper "Learning with AMIGo: Adversarially Motivated Intrinsic Goals".☆61Updated last year
- Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"☆125Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆64Updated 4 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆37Updated last year
- Autoregressive Energy Machines☆77Updated last year
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- Stein Variational Policy Gradient for REINFORCE☆17Updated 7 years ago
- ☆61Updated last year
- Automatically Composing Representation Transformations as a Means for Generalization☆24Updated 5 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Deconfounding Reinforcement Learning in Observational Settings☆48Updated 5 years ago
- ☆65Updated 4 years ago
- ☆65Updated 3 months ago