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Official repository for the Boltz biomolecular interaction models
Multi-domain Distribution Learning for De Novo Drug Design
Computational Fluid Dynamics based on PyTorch and the Lattice Boltzmann Method
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.
The property-based testing library for Python
A unified framework for machine learning collective variables for enhanced sampling simulations
Graphormer is a general-purpose deep learning backbone for molecular modeling.
Geometric GNN Dojo provides unified implementations and experiments to explore the design space of Geometric Graph Neural Networks (ICML 2023)
A playbook for systematically maximizing the performance of deep learning models.
MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
Robust representation of semantically constrained graphs, in particular for molecules in chemistry
Interpolating natural cubic splines. Includes batching, GPU support, support for missing values, evaluating derivatives of the spline, and backpropagation.
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
A python module for manipulating cartesian and internal coordinates.
TorchANI 2.0 is an open-source library that supports training, development, and research of ANI-style neural network interatomic potentials. It was originally developed and is currently maintained …
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
Deep learning quantum Monte Carlo for electrons in real space
Official Code for Invertible Residual Networks
OpenMM is a toolkit for molecular simulation using high performance GPU code.