XinjianOUYANG

dm-haiku

JAX-based neural network library

Dans_Diffraction

Reads crystallographic cif files and simulates diffraction

DiffuseCode

Suite of programs to simulate disordered and nanomaterials

deepxde

A library for scientific machine learning and physics-informed learning

torchdyn

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

chemtrain

Training Molecular Dynamics Potentials in JAX

Fused-EXP-DFT-MLP

difftre

Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting

DiT

Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

neural-ode

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

awesome-AI4EDA

This repo awesome-AI4EDA contains the source for the webpage: https://ai4eda.github.io, which is a curated paper list of awesome AI for EDA.

AutoForce

Sparse Gaussian Process Potentials

PhiFlow

A differentiable PDE solving framework for machine learning

LeftNet

powerxrd

A Python package build to analyze powder XRD (and XRD) data. The only known open-source Github project with a Rietveld refinement method in development.

dscribe

DScribe is a python package for creating machine learning descriptors for atomistic systems.

circumventing_data_imbalance_magmom_predictions

This repository houses all the code and data that should allow for the reproduction of the results in the paper: "Circumventing Data Imbalance in Magnetic Ground State Data for Magnetic Moment Predictions"

circuit_training

3

GPU-accelerated micromagnetic simulator

chgnet

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

llg

This repository provides a library to solve the LLG equation by using the Heun schema. Also, it provides a CLI to run the library.

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

MLCAD-2023-FPGA-Macro-Placement-Contest

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

MicroElectronics

微电子学自学计划

CircuitNet

CircuitNet: An Open-Source Dataset for Machine Learning Applications in Electronic Design Automation (EDA)

pytorch_geometric

Graph Neural Network Library for PyTorch

jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

mace

MACE - Fast and accurate machine learning interatomic potentials with higher order equivariant message passing.