HannesStark
MIT PhD student • Geometric ML + ML for molecules
Massachusetts Institute of TechnologyCambridge, MA
HannesStark's Stars
ManimCommunity/manim
A community-maintained Python framework for creating mathematical animations.
google-deepmind/alphafold
Open source code for AlphaFold.
gruns/icecream
🍦 Never use print() to debug again.
dwyl/learn-to-send-email-via-google-script-html-no-server
:email: An Example of using an HTML form (e.g: "Contact Us" on a website) to send Email without a Backend Server (using a Google Script) perfect for static websites that need to collect data.
benedekrozemberczki/pytorch_geometric_temporal
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
rdkit/rdkit
The official sources for the RDKit library
graphdeeplearning/benchmarking-gnns
Repository for benchmarking graph neural networks
snap-stanford/ogb
Benchmark datasets, data loaders, and evaluators for graph machine learning
divelab/DIG
A library for graph deep learning research
lucidrains/byol-pytorch
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
ChandlerBang/awesome-self-supervised-gnn
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
DeepGraphLearning/torchdrug
A powerful and flexible machine learning platform for drug discovery
rdevon/DIM
Deep InfoMax (DIM), or "Learning Deep Representations by Mutual Information Estimation and Maximization"
Open-Catalyst-Project/ocp
Open Catalyst Project's library of machine learning methods for catalysis
chaitjo/efficient-gnns
Code and resources on scalable and efficient Graph Neural Networks
FabianFuchsML/se3-transformer-public
code for the SE3 Transformers paper: https://arxiv.org/abs/2006.10503
datamol-io/datamol
Molecular Processing Made Easy.
vgsatorras/egnn
lukecavabarrett/pna
Implementation of Principal Neighbourhood Aggregation for Graph Neural Networks in PyTorch, DGL and PyTorch Geometric
joshr17/HCL
ICLR 2021, Contrastive Learning with Hard Negative Samples
learningmatter-mit/geom
GEOM: Energy-annotated molecular conformations
danielzuegner/code-transformer
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".
PattanaikL/GeoMol
twitter-research/cwn
Message Passing Neural Networks for Simplicial and Cell Complexes
DevinKreuzer/SAN
Saro00/DGN
Implementation of Directional Graph Networks in PyTorch and DGL
inria-thoth/GraphiT
Official Pytorch Implementation of GraphiT
patonlab/CASCADE
CAlculation of NMR Chemical Shifts using Deep LEarning
joshr17/IFM
Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.
gncs/graphdg
Generative model for molecular distance geometry