HannesStark
MIT PhD student • Geometric ML + ML for molecules
Massachusetts Institute of TechnologyCambridge, MA
HannesStark's Stars
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.
atong01/conditional-flow-matching
TorchCFM: a Conditional Flow Matching library
gcorso/DiffDock
Implementation of DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
RexYing/gnn-model-explainer
gnn explainer
RobertTLange/gymnax
RL Environments in JAX 🌍
GFNOrg/gflownet
Generative Flow Networks
hpcaitech/FastFold
Optimizing AlphaFold Training and Inference on GPU Clusters
Shen-Lab/GraphCL
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
shchur/gnn-benchmark
Framework for evaluating Graph Neural Network models on semi-supervised node classification task
yataobian/awesome-ebm
Collecting research materials on EBM/EBL (Energy Based Models, Energy Based Learning)
gcorso/torsional-diffusion
Implementation of Torsional Diffusion for Molecular Conformer Generation (NeurIPS 2022)
nnaisense/bayesian-flow-networks
This is the official code release for Bayesian Flow Networks.
vijaydwivedi75/gnn-lspe
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
octavian-ganea/equidock_public
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
ketatam/DiffDock-PP
Implementation of DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models in PyTorch (ICLR 2023 - MLDD Workshop)
TUM-DAML/gemnet_pytorch
GemNet model in PyTorch, as proposed in "GemNet: Universal Directional Graph Neural Networks for Molecules" (NeurIPS 2021)
divelab/MoleculeX
cptq/SignNet-BasisNet
SignNet and BasisNet
borchero/natural-posterior-network
Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, 2022)
ghliu/SB-FBSDE
Likelihood Training of Schrödinger Bridge using FBSDEs Theory, ICLR 2022
sharpenb/Posterior-Network
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
jctops/understanding-oversquashing
mle-infrastructure/mle-scheduler
Lightweight Cluster/Cloud VM Job Management 🚀
stadlmax/Graph-Posterior-Network
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
LarsHoldijk/SOCTransitionPaths
FelixOpolka/pnerf-pytorch
🔗 PyTorch implementation of the Parallelized Natural Extension Reference Frame algorithm
blondegeek/e3nn
A modular framework for neural networks with Euclidean symmetry
bkmi/equivariant-benchmark
Benchmarking equivariant neural networks.
Ahmed-A-A-Elhag/GAD
LioLab/liolab.github.io