Code for reproducing results in "Generative Model with Dynamic Linear Flow"

[NeurIPS 2024] Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow

A repository for the final project implementing/applying Boltzmann generators for Computational Statistical Physics (PHYS 7810) at CU Boulder

Library about construction helper for Generative models e.g. Flow-based Model with Tensorflow 2.x.

BSc Project - Amirkabir University of Technology - Winter 2023

[NeurIPS 2023] Training Energy-Based Normalizing Flow with Score-Matching Objectives

Flow-based continuous hidden Markov models

[INFOCOM 2024]: Official Implementation of "Routing-Oblivious Network Tomography with Flow-Based Generative Model"

Code for artificial toy data sets used to evaluate (conditional) invertible neural networks and related methods

Official repository of FlowAlign

A library for constructing specialized neural networks for Bayesian parameter inference (invertible networks) and Bayesian model selection (evidential networks).

Code for the paper "Guided Image Generation with Conditional Invertible Neural Networks" (2019)

Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)

A comprehensive collection of research papers and resources on diffusion&flow based models, systematically organized by application and architecture. It highlights cutting-edge advances in flow-guided diffusion techniques for image, video, and multimodal generation.

Solving inverse problems using conditional invertible neural networks.