Tristan Deleu

pytorch-meta. A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

pytorch-maml-rl. Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch

ntm-one-shot. One-shot Learning with Memory-Augmented Neural Networks

pytorch-maml. An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta

jax-dag-gflownet. Code for "Bayesian Structure Learning with Generative Flow Networks"

jax-comln. Code for "Continuous-Time Meta-Learning with Forward Mode Differentiation" (ICLR 2022)

jax-meta-learning. A collection of meta-learning algorithms in Jax

gfn-maxent-rl. Comparison between GFlowNets & Maximum Entropy RL

switching-kalman-filter. Python implementation of the Switching Kalman Filter

pytorch-structured-sparsity. Code for "Structured Sparsity Inducing Adaptive Optimizers for Deep Learning" in PyTorch

jax-jsp-gfn. Official code for the paper "Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network"

neural-gpu. Theano implementation of the Neural GPU

metax. A collection of extensions for meta-learning in JAX

tips-research-mila. General tips to drive your research at Mila

gflownet-bib. Bibtex file for related work in GFlowNet

synergies-disentanglement-sparsity. Official code for the paper "Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning" (ICML 2023)

Awesome-GFlowNets. A curated list of resources about generative flow networks (GFlowNets).

gfn. Python

transformers. 🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

pgmpy. Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.

rlpyt. Reinforcement Learning in PyTorch