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GPU-accelerated micromagnetic simulator

aenet-lammps

This package provides the interface module between aenet [1] and LAMMPS [2], patch of aenet for the LAMMPS library, and Artificial Neural network (ANN) potential parameter file of BCC iron.

att_gconvs

Code repository for the paper "Attentive Group Equivariant Convolutional Neural Networks" published at ICML 2020. https://arxiv.org/abs/2002.03830

autoforce

Sparse Gaussian Process Potentials

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.

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-quantum-computing

A curated list of awesome quantum computing learning and developing resources.

awesome_ai4eda

bigdl

Fast, distributed, secure AI for Big Data

cdvae

An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

cgcnn

Crystal graph convolutional neural networks for predicting material properties.

chemtrain

Training Molecular Dynamics Potentials in JAX

chgnet

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

circuit_training

circuitnet

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

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"

cuda-handbook

pdf

dadapy

Distance-based Analysis of DAta-manifolds in python

dans_diffraction

Reads crystallographic cif files and simulates diffraction

deeph-pack

Deep neural networks for density functional theory Hamiltonian.

deeplearning

深度学习教程, 优秀文章

deepmd-kit

A deep learning package for many-body potential energy representation and molecular dynamics

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deepxde

A library for scientific machine learning and physics-informed learning

dgl

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

difftre

Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting

diffusecode

Suite of programs to simulate disordered and nanomaterials

diffusion-probabilistic-models

Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

dimenet

DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules" (NeurIPS-W 2020)