Gabriele Corso

According to our database, Gabriele Corso authored at least 19 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Deep Confident Steps to New Pockets: Strategies for Docking Generalization.

Gabriele Corso, Arthur Deng, Benjamin Fry, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola

CoRR, 2024

DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents.

Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Dirichlet Flow Matching with Applications to DNA Sequence Design.

Hannes Stärk, Bowen Jing, Chenyu Wang, Gabriele Corso, Bonnie Berger, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models.

Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Confident Steps to New Pockets: Strategies for Docking Generalization.

Gabriele Corso, Arthur Deng, Nicholas Polizzi, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

DiffDock-PP: Rigid Protein-Protein Docking with Diffusion Models.

Mohamed Amine Ketata, Cedrik Laue, Ruslan Mammadov, Hannes Stärk, Menghua Wu, Gabriele Corso, Céline Marquet, Regina Barzilay, Tommi S. Jaakkola

CoRR, 2023

EigenFold: Generative Protein Structure Prediction with Diffusion Models.

Bowen Jing, Ezra Erives, Peter Pao-Huang, Gabriele Corso, Bonnie Berger, Tommi S. Jaakkola

CoRR, 2023

Modeling Molecular Structures with Intrinsic Diffusion Models.

Gabriele Corso

CoRR, 2023

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking.

Gabriele Corso, Hannes Stärk, Bowen Jing, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Graph Anisotropic Diffusion.

Ahmed A. A. Elhag, Gabriele Corso, Hannes Stärk, Michael M. Bronstein

CoRR, 2022

Torsional Diffusion for Molecular Conformer Generation.

Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The First Learning on Graphs Conference: Preface.

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

Proceedings of the Learning on Graphs Conference, 2022

Learning Graph Search Heuristics.

Michal Pándy, Weikang Qiu, Gabriele Corso, Petar Velickovic, Zhitao Ying, Jure Leskovec, Pietro Liò

Proceedings of the Learning on Graphs Conference, 2022

3D Infomax improves GNNs for Molecular Property Prediction.

Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió

Proceedings of the International Conference on Machine Learning, 2022

Subspace Diffusion Generative Models.

Bowen Jing, Gabriele Corso, Renato Berlinghieri, Tommi S. Jaakkola

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

ICLR 2021 Challenge for Computational Geometry & Topology: Design and Results.

Nina Miolane, Matteo Caorsi, Umberto Lupo, Marius Guerard, Nicolas Guigui, Johan Mathe, Yann Cabanes, Wojciech Reise, Thomas Davies, António Leitão, Somesh Mohapatra, Saiteja Utpala, Shailja Shailja, Gabriele Corso, Guoxi Liu, Federico Iuricich, Andrei Manolache, Mihaela Nistor, Matei Bejan, Armand Mihai Nicolicioiu, Bogdan-Alexandru Luchian, Mihai-Sorin Stupariu, Florent Michel, Khanh Dao Duc, Bilal Abdulrahman, Maxim Beketov, Elodie Maignant, Zhiyuan Liu, Marek Cerný, Martin Bauw, Santiago Velasco-Forero, Jesús Angulo, Yanan Long

CoRR, 2021

Neural Distance Embeddings for Biological Sequences.

Gabriele Corso, Zhitao Ying, Michal Pándy, Petar Velickovic, Jure Leskovec, Pietro Liò

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Directional Graph Networks.

Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Principal Neighbourhood Aggregation for Graph Nets.

Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020