noegroup / stochastic_normalizing_flowsLinks
Stochastic Normalizing Flows
☆76Updated 3 years ago
Alternatives and similar repositories for stochastic_normalizing_flows
Users that are interested in stochastic_normalizing_flows are comparing it to the libraries listed below
Sorting:
- Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.☆58Updated last year
- Library for normalizing flows and neural flows.☆24Updated 3 years ago
- Implementation of Action Matching☆44Updated 2 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 2 years ago
- PyTorch implementation of the OT-Flow approach in arXiv:2006.00104☆53Updated 11 months ago
- Likelihood Training of Schrödinger Bridge using FBSDEs Theory, ICLR 2022☆84Updated 3 years ago
- ☆52Updated 2 years ago
- Official repository for "Categorical Normalizing Flows via Continuous Transformations"☆56Updated 4 years ago
- Implementation of Action Matching for the Schrödinger equation☆24Updated 2 years ago
- Normalizing Flows using JAX☆83Updated last year
- Regularized Neural ODEs (RNODE)☆82Updated 3 years ago
- ☆68Updated 2 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- ☆17Updated 3 years ago
- Deterministic particle dynamics for simulating Fokker-Planck probability flows☆24Updated 2 years ago
- Score-based generative models for compact manifolds☆111Updated last year
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆32Updated 3 years ago
- Discrete Normalizing Flows implemented in PyTorch☆114Updated 3 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)☆119Updated last year
- Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral☆48Updated 2 years ago
- [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".☆35Updated 6 months ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆38Updated 2 years ago
- Collecting research materials on neural samplers with diffusion/flow models☆52Updated 3 weeks ago
- PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…☆24Updated last year
- GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134☆23Updated 3 years ago
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆55Updated last year
- A minimalist implementation of score-based diffusion model☆127Updated 3 years ago