A high-performance toolkit for atomistic simulations in JAX.

Implementing Controlled Monte Carlo Diffusions (ICLR 2024)

A repo for transferable sampling of molecular systems

Benchmark Blackjax samplers on Inference Gym models

ALCHEMI Toolkit-Ops is a collection of optimized batch kernels to accelerate computational chemistry and material science workflows.

Continuously Tempered Diffusion Samplers

code for adjoint-based diffusion samplers

Official Implementation of "Variational Flow Maps: Make Some Noise for One-Step Conditional Generation"

Improved sampling via learned diffusions (ICLR2024) and an optimal control perspective on diffusion-based generative modeling (TMLR2024)

Official repository of Zatom-1, a multimodal flow foundation model for 3D molecules and materials

graph2mat: Graph to matrix conversion

The Spacetime of Diffusion Models: An Information Geometry Perspective (ICLR 2026 Oral)

Lagrangian formulation of Doob's h-transform allowing for efficient rare event sampling

Codebase for https://arxiv.org/abs/2412.07081

Official Implementation of "Meta Flow Maps enable scalable reward alignment"

HIP: Hessians with Interatomic Potentials

[NeurIPS 2025 Spotlight] E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products

A framework for training energy-based diffusion models for sampling and energy estimation.

CHARMM and AMBER forcefields for OpenMM (with small molecule support)

[ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".

AIMNet2: Fast and accurate machine-learned interatomic potential for molecular dynamics simulations

DEPRECATED — migrated to isayevlab/aimnetcentral

Code for computing vibration data and Gibbs corrections from vasp OUTCARS and with fairchem open catalyst machine learning potentials..

A high-performance, GPU-accelerated library for key computational chemistry tasks, such as molecular similarity, conformer generation, and geometry relaxation.

Muon is an optimizer for hidden layers in neural networks

Thermal and photochemical reaction path optimization and discovery

Source codes for paper "Harnessing Machine Learning to Enhance Transition State Search with Interatomic Potentials and Generative Models"