Alternatives and similar repositories for NeuralWassersteinGradientFlows:

Users that are interested in NeuralWassersteinGradientFlows are comparing it to the libraries listed below

• J-zin / energy-discrepancy
  NeurIPS'23: Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
  ☆16Updated 6 months ago
• federicobergamin / riemannian-laplace-approximation
  Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"
  ☆11Updated last year
• chenw20 / SGPA
  Example code of Sparse Gaussian Process Attention (ICLR 2023)
  ☆24Updated 9 months ago
• TianrongChen / DMSB
  Official implementation of Deep Momentum Schrödinger Bridge
  ☆25Updated last year
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 2 years ago
• necludov / jam
  Implementation of Action Matching
  ☆41Updated last year
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆30Updated 4 months ago
• Wenlin-Chen / DiGS
  Official PyTorch implementation of Diffusive Gibbs Sampler (DiGS), proposed in the paper Diffusive Gibbs Sampling (published at ICML 2024…
  ☆10Updated 8 months ago
• ngushchin / EntropicNeuralOptimalTransport
  Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).
  ☆37Updated last year
• ngushchin / EntropicOTBenchmark
  Entropic Optimal Transport Benchmark (NeurIPS 2023).
  ☆23Updated last year
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 2 years ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆47Updated 4 years ago
• sbyebss / variational_wgf
  [ICML2022] Variational Wasserstein gradient flow
  ☆22Updated 2 years ago
• gnobitab / ConstrainedDiffusionBridge
  ☆12Updated 2 years ago
• zdhNarsil / Diffusion-Generative-Flow-Samplers
  PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…
  ☆24Updated last year
• take-koshizuka / NLSB
  ☆19Updated 2 months ago
• ermongroup / dre-infinity
  Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)
  ☆19Updated 3 years ago
• noamroze / moser_flow
  ☆17Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆99Updated last year
• angusphillips / particle_denoising_diffusion_sampler
  Code repository for Particle Denoising Diffusion Sampler
  ☆13Updated last year
• J-zin / Awesome-Diffusion-Flow-Samplers
  Collecting research materials on neural samplers with diffusion/flow models
  ☆46Updated last month
• tung-nd / ExPT
  ☆16Updated last year
• vdeborto / cdsb
  ☆23Updated 2 years ago
• franciscovargas / denoising_diffusion_samplers
  ☆16Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆46Updated 2 years ago
• AndyShih12 / mac
  PyTorch implementation for "Training and Inference on Any-Order Autoregressive Models the Right Way", NeurIPS 2022 Oral, TPM 2023 Best Pa…
  ☆14Updated last year
• volagold / fce-2d
  Flow Contrastive Estimation (FCE) PyTorch Implementation on 2D data
  ☆10Updated 2 years ago
• GFNOrg / gfn-diffusion
  ☆28Updated 3 weeks ago
• marc-h-lambert / W-VI
  The companion code for the paper "Variational inference via Wasserstein gradient flows (W-VI) M. Lambert, S. Chewi, F. Bach, S. Bonnabel…
  ☆12Updated 2 years ago