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Hannes Stärk
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2020 – today
- 2024
- [j1]Ilia Igashov, Hannes Stärk, Clément Vignac, Arne Schneuing, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-conditional diffusion model for molecular linker design. Nat. Mac. Intell. 6(4): 417-427 (2024) - [c7]Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design. ICML 2024 - [c6]Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola:
Dirichlet Flow Matching with Applications to DNA Sequence Design. ICML 2024 - [i14]Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola:
Dirichlet Flow Matching with Applications to DNA Sequence Design. CoRR abs/2402.05841 (2024) - [i13]Bowen Jing, Hannes Stärk, Tommi S. Jaakkola, Bonnie Berger:
Generative Modeling of Molecular Dynamics Trajectories. CoRR abs/2409.17808 (2024) - 2023
- [c5]Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. ICLR 2023 - [c4]Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan:
The Second Learning on Graphs Conference: Preface. LoG 2023: i-xix - [i12]Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao:
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR abs/2301.11517 (2023) - [i11]Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stärk, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola:
DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models. CoRR abs/2304.03889 (2023) - [i10]Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i9]Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design. CoRR abs/2310.05764 (2023) - [i8]Michael Plainer, Hannes Stärk, Charlotte Bunne, Stephan Günnemann:
Transition Path Sampling with Boltzmann Generator-based MCMC Moves. CoRR abs/2312.05340 (2023) - 2022
- [c3]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió:
3D Infomax improves GNNs for Molecular Property Prediction. ICML 2022: 20479-20502 - [c2]Hannes Stärk, Octavian Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi S. Jaakkola:
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction. ICML 2022: 20503-20521 - [c1]Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov:
The First Learning on Graphs Conference: Preface. LoG 2022: i-xxiii - [i7]Hannes Stärk, Octavian-Eugen Ganea, Lagnajit Pattanaik, Regina Barzilay, Tommi S. Jaakkola:
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction. CoRR abs/2202.05146 (2022) - [i6]Ahmed A. A. Elhag, Gabriele Corso, Hannes Stärk, Michael M. Bronstein:
Graph Anisotropic Diffusion. CoRR abs/2205.00354 (2022) - [i5]Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola:
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. CoRR abs/2210.01776 (2022) - [i4]Ilia Igashov, Hannes Stärk, Clément Vignac, Victor Garcia Satorras, Pascal Frossard, Max Welling, Michael M. Bronstein, Bruno E. Correia:
Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design. CoRR abs/2210.05274 (2022) - [i3]Sohir Maskey, Ali Parviz, Maximilian Thiessen, Hannes Stärk, Ylli Sadikaj, Haggai Maron:
Generalized Laplacian Positional Encoding for Graph Representation Learning. CoRR abs/2210.15956 (2022) - 2021
- [i2]Zekarias T. Kefato, Sarunas Girdzijauskas, Hannes Stärk:
Jointly Learnable Data Augmentations for Self-Supervised GNNs. CoRR abs/2108.10420 (2021) - [i1]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Liò:
3D Infomax improves GNNs for Molecular Property Prediction. CoRR abs/2110.04126 (2021)
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