Alternatives and similar repositories for energy-discrepancy

Users that are interested in energy-discrepancy are comparing it to the libraries listed below

• vdeborto / cdsb
  ☆24Updated 3 years ago
• necludov / action-matching
  Implementation of Action Matching for the Schrödinger equation
  ☆25Updated 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…
  ☆26Updated last year
• take-koshizuka / NLSB
  ☆21Updated 10 months ago
• sbyebss / variational_wgf
  [ICML2022] Variational Wasserstein gradient flow
  ☆24Updated 3 years ago
• CW-Huang / sdeflow-light
  A minimalist implementation of score-based diffusion model
  ☆129Updated 4 years ago
• GFNOrg / gfn-diffusion
  ☆35Updated 8 months ago
• vdutor / neural-diffusion-processes
  Neural Diffusion Processes
  ☆81Updated last year
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆39Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆10Updated 3 years ago
• DenisBless / variational_sampling_methods
  [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".
  ☆40Updated last year
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆23Updated 3 years ago
• TianrongChen / DMSB
  Official implementation of Deep Momentum Schrödinger Bridge
  ☆27Updated 2 years ago
• VincentStimper / resampled-base-flows
  Normalizing Flows with a resampled base distribution
  ☆47Updated 3 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…
  ☆15Updated 2 years ago
• ghliu / SB-FBSDE
  Likelihood Training of Schrödinger Bridge using FBSDEs Theory, ICLR 2022
  ☆87Updated 3 years ago
• iamalexkorotin / Wasserstein2Benchmark
  A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)
  ☆45Updated 3 years ago
• ngushchin / EntropicOTBenchmark
  Entropic Optimal Transport Benchmark (NeurIPS 2023).
  ☆27Updated last year
• noegroup / stochastic_normalizing_flows
  Stochastic Normalizing Flows
  ☆78Updated 4 years ago
• necludov / wl-mechanics
  ☆31Updated last year
• juliusberner / sde_sampler
  Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (TMLR2024)
  ☆70Updated 8 months ago
• facebookresearch / SOC-matching
  Code release for "Stochastic Optimal Control Matching"
  ☆39Updated last year
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 3 years ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆52Updated 3 years ago
• necludov / jam
  Implementation of Action Matching
  ☆48Updated 2 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 4 years ago
• ngushchin / EntropicNeuralOptimalTransport
  Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).
  ☆39Updated last year
• htlambley / functional_autoencoders
  Autoencoders in Function Space: Resolution-invariant autoencoders for functional data based on the functional variational autoencoder (FV…
  ☆29Updated this week
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆57Updated last year
• J-zin / Awesome-Diffusion-Flow-Samplers
  Collecting research materials on neural samplers with diffusion/flow models
  ☆59Updated 5 months ago