Abhivega's Stars
Chemellia/AtomicGraphNets.jl
Atomic graph models for molecules and crystals in Julia
dsgiitr/graph_nets
PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.
taneishi/EBM_torch
Energy Based Models in PyTorch
andrepxx/go-dsp-guitar
A cross-platform multichannel multi-effects processor for electric guitars and other instruments.
pranabdas/fullprof
Powder X-ray diffraction Rietveld refinement using FullProf
stitchfix/hamilton
A scalable general purpose micro-framework for defining dataflows. THIS REPOSITORY HAS BEEN MOVED TO www.github.com/dagworks-inc/hamilton
McWilliamsCenter/slurm_jupyter
Brief notes on how to run and access a jupyter notebook on a login node and a compute node using the SLURM cluster scheduler
materials/mint
Materials Interface: methods in computational materials science
sirmarcel/asax
ase + jax-md = asax
cthoyt/pystow
👜 Easily pick a place to store data for your Python code.
MADICES/mapping-spectrum-to-structure
petermr/pygetpapers
a Python version of getpapers
tilde-lab/awesome-materials-informatics
Curated list of known efforts in materials informatics, i.e. in modern materials science
nschloe/awesome-scientific-computing
:sunglasses: Curated list of awesome software for numerical analysis and scientific computing
nschloe/matplotx
:bar_chart: More styles and useful extensions for Matplotlib
jaakkopasanen/AutoEq
Automatic headphone equalization from frequency responses
ncfrey/resources
A Highly Opinionated List of Open Source Materials Informatics Resources
samoturk/mol2vec
Mol2vec - an unsupervised machine learning approach to learn vector representations of molecular substructures
rdkit/rdkit
The official sources for the RDKit library
materialsvirtuallab/mlearn
Benchmark Suite for Machine Learning Interatomic Potentials for Materials
dense-analysis/ale
Check syntax in Vim/Neovim asynchronously and fix files, with Language Server Protocol (LSP) support
amirhajibabaei/AutoForce
Sparse Gaussian Process Potentials
ulissigroup/vasp-interactive
pypr/compyle
Execute a subset of Python on HPC platforms
atomisticnet/aenet
Atomic interaction potentials based on artificial neural networks
atomisticnet/MLP-beginners-guide
Strategies for the Construction of Neural-Network Based Machine-Learning Potentials (MLPs)
njszym/XRD-AutoAnalyzer
megvii-research/DPGN
[CVPR 2020] DPGN: Distribution Propagation Graph Network for Few-shot Learning.
AntonioLonga/PytorchGeometricTutorial
Pytorch Geometric Tutorials
materialsvirtuallab/megnet
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals