Alternatives and similar repositories for normalizing-flows

Users that are interested in normalizing-flows are comparing it to the libraries listed below

• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 2 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 2 weeks ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆103Updated last year
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆76Updated 3 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆48Updated last week
• necludov / jam
  Implementation of Action Matching
  ☆44Updated 2 years ago
• DanieleGammelli / pyro-torch-normalizing-flows
  Implementations of Normalizing Flows in Pytorch/Pyro
  ☆19Updated 5 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆121Updated 3 years ago
• mfinzi / olive-oil-ml
  ☆14Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• TyXe-BDL / TyXe
  ☆152Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆66Updated last month
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆52Updated 2 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆38Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆170Updated 3 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆51Updated last year
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 3 years ago
• mbilos / stribor
  Library for normalizing flows and neural flows.
  ☆24Updated 3 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆53Updated 11 months ago
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆85Updated 6 months ago
• lollcat / fab-torch
  Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.
  ☆58Updated last year
• MachineLearningLifeScience / stochman
  Algorithms for computations on random manifolds made easier
  ☆90Updated last year
• NickHunt-Smith / MCMC-diffusion
  A Metropolis-Hastings MCMC sampler accelerated via diffusion models
  ☆13Updated 11 months ago
• hakeemtonalli / deep-kernel-learning
  Implementation of deep kernels in GPyTorch and Pyro
  ☆10Updated 4 years ago
• dimitra-maoutsa / odes_for_sdes
  Deterministic particle dynamics for simulating Fokker-Planck probability flows
  ☆24Updated 2 years ago
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆20Updated 3 years ago
• J-zin / Awesome-Diffusion-Flow-Samplers
  Collecting research materials on neural samplers with diffusion/flow models
  ☆52Updated 3 weeks ago