A modular, easy to extend GFlowNet library

GFlowNet library specialized for graph & molecular data

Generative Flow Networks - GFlowNet

DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks

A PyTorch implementation of a Generative Flow Network (GFlowNet) proposed by Bengio et al. (2021)

Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.

Repository for "Generative Flow Networks as Entropy-Regularized RL" (AISTATS-2024, Oral)

A collection of deep reinforcement learning-based & GFlowNet drug molecule generators focused on generation of molecules using Graphs/SELFIES guided by modern retrosynthesis tools to increase synthetic accessibility of de-novo designed drugs.

A deep reinforcement learning framework for generating formulaic alpha factors for quantitative investment, powered by GFlowNet, implemented in Python&PyTorch.

Investigating Generalization Behaviours of Generative Flow Networks

Synthesis-oriented generative model to discover diverse drug candidates through a large action space and GFlowNet objective.

A simple implementation of a GFlowNet using PyTorch

Code for implementing GFlowOut for medical images, to improve uncertainty predictions.