Підписатись
Hannes Stark
Hannes Stark
Інші іменаHannes Staerk, Hannes Stärk
PhD Student, MIT
Підтверджена електронна адреса в mit.edu - Домашня сторінка
Назва
Посилання
Посилання
Рік
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
G Corso, H Stärk, B Jing, R Barzilay, T Jaakkola
ICLR 2023: International Conference on Learning Representations (full paper)., 2023
5422023
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
H Stärk, OE Ganea, L Pattanaik, R Barzilay, T Jaakkola
ICML 2022: International Conference on Machine Learning (full paper). Also …, 2022
3242022
3D Infomax improves GNNs for Molecular Property Prediction
H Stärk, D Beaini, G Corso, P Tossou, C Dallago, S Günnemann, P Liò
ICML 2022: International Conference on Machine Learning (full paper). Also …, 2022
2602022
Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery
F Wong, A Krishnan, EJ Zheng, H Stärk, AL Manson, AM Earl, T Jaakkola, ...
Molecular systems biology 18 (9), e11081, 2022
1702022
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design
I Igashov, H Stärk, C Vignac, VG Satorras, P Frossard, M Welling, ...
Under review. arXiv preprint https://arxiv.org/abs/2210.05274, 2022
1602022
Light Attention Predicts Protein Location from the Language of Life
H Stärk, C Dallago, M Heinzinger, B Rost
Bioinformatics Advances. Also at 2 ICLR'21 Workshops, 1 ICML'21 Workshop …, 2021
1142021
Graph neural networks
G Corso, H Stark, S Jegelka, T Jaakkola, R Barzilay
Nature Reviews Methods Primers 4 (1), 17, 2024
602024
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models
MA Ketata, C Laue, R Mammadov, H Stärk, M Wu, G Corso, C Marquet, ...
arXiv preprint arXiv:2304.03889, 2023
462023
Dirichlet Flow Matching with Applications to DNA Sequence Design
H Stark, B Jing, C Wang, G Corso, B Berger, R Barzilay, T Jaakkola
ICML 2024; also Spotlight at ICLR 2024 MLGenX workshop, 2024
352024
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design
H Stärk, B Jing, R Barzilay, T Jaakkola
ICML 2024; also Spotlight at NeurIPS 2023 AI4Science Workshop, 2023
192023
Generalized laplacian positional encoding for graph representation learning
S Maskey, A Parviz, M Thiessen, H Stärk, Y Sadikaj, H Maron
NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022
142022
PLINDER: The protein-ligand interactions dataset and evaluation resource
J Durairaj, Y Adeshina, Z Cao, X Zhang, V Oleinikovas, T Duignan, ...
bioRxiv, 2024.07. 17.603955, 2024
122024
DiffDock-Pocket: Diffusion for Pocket-Level Docking with Sidechain Flexibility
M Plainer, M Toth, S Dobers, H Stark, G Corso, C Marquet, R Barzilay
92023
Generative Modeling of Molecular Dynamics Trajectories
B Jing, H Stärk, T Jaakkola, B Berger
NeurIPS 2024, 2024
72024
Blind protein-ligand docking with diffusion-based deep generative models
G Corso, B Jing, H Stark, R Barzilay, T Jaakkola
Biophysical Journal 122 (3), 143a, 2023
62023
Transition Path Sampling with Boltzmann Generator-based MCMC Moves
M Plainer, H Stärk, C Bunne, S Günnemann
Oral at GenBio Workshop (NeurIPS 2023), 2023
42023
Jointly Learnable Data Augmentations for Self-Supervised GNNs
ZT Kefato, S Girdzijauskas, H Stärk
SSL Workshop at NeurIPS 2021, 2021
42021
Latent Space Simulator for Unveiling Molecular Free Energy Landscapes and Predicting Transition Dynamics
S Dobers, H Stark, X Fu, D Beaini, S Günnemann
NeurIPS 2023 AI for Science Workshop, 2023
12023
Bio-Inspired Design of Conductive Heat Sinks Using a Generative Autoencoder Framework
MC Ignuta-Ciuncanu, H Stärk, R Martinez-Botas
Available at SSRN 4576761, 0
1
The First Learning on Graphs Conference: Preface
B Rieck, R Pascanu, Y Du, H Stärk, D Lim, CK Joshi, A Deac, I Duta, ...
Learning on Graphs Conference, i-xxiii, 2022
2022
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