Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.
☆68Mar 11, 2024Updated 2 years ago
Alternatives and similar repositories for fab-torch
Users that are interested in fab-torch are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Implementation of methods to sample from Boltzmann distributions☆22Jan 24, 2023Updated 3 years ago
- PyTorch implementation for our ICLR 2024 paper "Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory…☆26Dec 21, 2023Updated 2 years ago
- Flow Annealed Importance Sampling Bootstrap (FAB) with JAX.☆13Jun 12, 2024Updated 2 years ago
- ☆12Oct 15, 2023Updated 2 years ago
- code for "Adjoint Sampling: Highly Scalable Diffusion Samplers via Adjoint Matching"☆136Jul 24, 2025Updated 10 months ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- ☆18Sep 27, 2023Updated 2 years ago
- [ICLR 2022] Path integral sampler☆54Aug 21, 2023Updated 2 years ago
- Code for the paper Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.☆71Jun 5, 2026Updated last week
- Collecting research materials on neural samplers with diffusion/flow models☆59Jul 4, 2025Updated 11 months ago
- Reward fine-tuning for Stable Diffusion models based on stochastic optimal control, including Adjoint Matching☆69May 30, 2025Updated last year
- ☆53Feb 27, 2023Updated 3 years ago
- [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".☆50Dec 9, 2024Updated last year
- ☆13Dec 13, 2023Updated 2 years ago
- ☆25Mar 26, 2024Updated 2 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Free-form flows are a generative model training a pair of neural networks via maximum likelihood☆51Jun 26, 2025Updated 11 months ago
- Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (TMLR2024)☆75Mar 14, 2025Updated last year
- Annotated implementations of equivariant (graph) neural networks in Jax: EGNN, SEGNN, NequIP.☆43Mar 1, 2025Updated last year
- Lagrangian formulation of Doob's h-transform allowing for efficient rare event sampling☆58Mar 26, 2025Updated last year
- MCHMC: sampler from an arbitrary differentiable distribution☆77Dec 9, 2025Updated 6 months ago
- Stochastic Normalizing Flows☆79Dec 9, 2021Updated 4 years ago
- code for "Riemannian Flow Matching on General Geometries".☆307Mar 13, 2024Updated 2 years ago
- A simple implementation of Hamiltonian Monte Carlo in JAX.☆20Feb 8, 2024Updated 2 years ago
- ☆10Mar 31, 2023Updated 3 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- Boltzmann Generators and Normalizing Flows in PyTorch☆198Jan 30, 2024Updated 2 years ago
- ☆19May 20, 2025Updated last year
- ☆230Feb 21, 2026Updated 3 months ago
- FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation☆291Dec 10, 2024Updated last year
- Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"☆61Jul 4, 2023Updated 2 years ago
- Likelihood Training of Schrödinger Bridge using FBSDEs Theory, ICLR 2022☆93Feb 22, 2022Updated 4 years ago
- Gradient Based Nested Sampling☆21Feb 2, 2024Updated 2 years ago
- Proof-of-concept of global switching between numpy/jax/pytorch in a library.☆17Jun 18, 2024Updated last year
- Official implementation of our paper "Bidirectional Consistency Models"; and reproduced Improved Consistency Models (iCT).☆27May 10, 2025Updated last year
- Managed Database hosting by DigitalOcean • AdPostgreSQL, MySQL, MongoDB, Kafka, Valkey, and OpenSearch available. Automatically scale up storage and focus on building your apps.
- Implementing Controlled Monte Carlo Diffusions (ICLR 2024)☆18Sep 30, 2024Updated last year
- A Metropolis-Hastings MCMC sampler accelerated via diffusion models☆17Jul 25, 2024Updated last year
- PyTorch implementation of normalizing flow models☆952Aug 25, 2024Updated last year
- ☆19May 11, 2023Updated 3 years ago
- Meta learning addresses noisy and under-labeled data in machine learning-guided antibody engineering (https://doi.org/10.1016/j.cels.2023…☆23Aug 8, 2024Updated last year
- ☆42Sep 20, 2022Updated 3 years ago
- Official PyTorch implementation of NeurIPS 2022 paper "Invertible Monotone Operators for Normalizing Flows"☆15Nov 28, 2022Updated 3 years ago