nw7g14

nw7g14's Stars

• google-deepmind/flows_for_atomic_solids

  Language:Python462

• janosh/elementari

  Interactive browser visualizations for materials science: periodic tables, 3d crystal structures, Bohr atoms, nuclei, heatmaps, scatter plots.

  Language:TypeScript12912

• janosh/thermo

  Data-driven risk-conscious thermoelectric materials discovery

  Language:Python124

• janosh/matbench-discovery

  An evaluation framework for machine learning models simulating high-throughput materials discovery.

  Language:Python779

• janosh/torch-mnf

  Multiplicative Normalizing Flows in PyTorch.

  Language:Python233

• janosh/tikz

  TikZ figures for concepts in physics/chemistry/ML

  Language:TeX18825

• amirgholami/PyHessian

  PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

  Language:Jupyter Notebook647112

• VirtuosoResearch/Generalization-in-graph-neural-networks

  Measuring generalization properties of graph neural networks

  Language:Python121

• gerkone/segnn-jax

  Steerable E(3) GNN in jax

  Language:Python22

• chemsurajit/largeDFTdata

  Data for QM9 molecules and reactions with 76 functionals and 3 basis sets

  Language:Python6

• tensorflow/gnn

  TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

  Language:Python1.3k167

• naver/roma

  RoMa: A lightweight library to deal with 3D rotations in PyTorch.

  Language:Python46518

• lucidrains/egnn-pytorch

  Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch

  Language:Python39467

• MikeS96/bayes_statististics

  Bayesian Statistics MOOC by Coursera - Solutions in Python

  Language:Jupyter Notebook296

• microsoft/timewarp

  Timewarp is a research project using deep learning to accelerate molecular dynamics simulation.

  Language:Python332

• izmailovpavel/flowgmm

  Language:Shell14613

• anton-bushuiev/PPIformer

  Learning to design protein-protein interactions with enhanced generalization (ICLR24)

  Language:Jupyter Notebook394

• niklasschmitz/ad-kernels

  Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"

  Language:Jupyter Notebook121

• Chen-Cai-OSU/awesome-equivariant-network

  Paper list for equivariant neural network

  95599

• senya-ashukha/simple-equivariant-gnn

  A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

  Language:Python12212

• vgsatorras/egnn

  Language:Python38474

• ebekkers/awesome-equivariant-network

  Paper list for equivariant neural network

  2

• microsoft/AI2BMD

  AI-powered ab initio biomolecular dynamics simulation

  14714

• mrossinek/cobib

  Console Bibliography

  Language:Python404

• Exscientia/physicsml

  A package for all physics based/related models

  Language:Python401

• src47/multibax-sklearn

  Design space subset estimation using Bayesian algorithm execution with sklearn GP models

  Language:Jupyter Notebook16

• src47/materials-bax-gpflow

  Code accompanying "Targeted materials discovery using Bayesian algorithm execution"

  Language:Python2

• JaxGaussianProcesses/GPJax

  Gaussian processes in JAX.

  Language:Python39849

• phlippe/uvadlc_notebooks

  Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

  Language:Jupyter Notebook2.3k540

• whitead/dmol-book

  Deep learning for molecules and materials book

  Language:Jupyter Notebook594116