Principal Neighbourhood Aggregation for Graph Nets. - Gabriele Corso; Luca Cavalleri; Dominique Beaini; Pietro Liò; Petar Velickovic (NeurIPS, 2020)

Directional Graph Networks. - Dominique Beaini; Saro Passaro; Vincent Létourneau; William L. Hamilton; Gabriele Corso; Pietro Lió (ICML, 2021)

Neural Distance Embeddings for Biological Sequences. - Gabriele Corso; Zhitao Ying; Michal Pándy; Petar Velickovic; Jure Leskovec; Pietro Liò (NeurIPS, 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 001; António Leitão; Somesh Mohapatra; Saiteja Utpala; et al. (CoRR, 2021)

Subspace Diffusion Generative Models. - Bowen Jing; Gabriele Corso; Renato Berlinghieri; Tommi S. Jaakkola (ECCV (23), 2022)

3D Infomax improves GNNs for Molecular Property Prediction. - Hannes Stärk; Dominique Beaini; Gabriele Corso; Prudencio Tossou; Christian Dallago; Stephan Günnemann; Pietro Lió (ICML, 2022)

Learning Graph Search Heuristics. - Michal Pándy; Weikang Qiu; Gabriele Corso; Petar Velickovic; Zhitao Ying; Jure Leskovec; Pietro Liò (LoG, 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 001; Gabriele Corso; Leonardo Cotta; Yanqiao Zhu 001; et al. (LoG, 2022)

Torsional Diffusion for Molecular Conformer Generation. - Bowen Jing; Gabriele Corso; Jeffrey Chang; Regina Barzilay; Tommi S. Jaakkola (NeurIPS, 2022)

Graph Anisotropic Diffusion. - Ahmed A. A. Elhag; Gabriele Corso; Hannes Stärk; Michael M. Bronstein (CoRR, 2022)

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. - Gabriele Corso; Hannes Stärk; Bowen Jing; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2023)

Modeling Molecular Structures with Intrinsic Diffusion Models. - Gabriele Corso (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)

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)

Deep Confident Steps to New Pockets: Strategies for Docking Generalization. - Gabriele Corso; Arthur Deng; Nicholas Polizzi; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2024)

Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. - Gabriele Corso; Yilun Xu; Valentin De Bortoli; Regina Barzilay; Tommi S. Jaakkola (ICLR, 2024)

Dirichlet Flow Matching with Applications to DNA Sequence Design. - Hannes Stärk; Bowen Jing; Chenyu Wang 003; Gabriele Corso; Bonnie Berger; Regina Barzilay; Tommi S. Jaakkola (ICML, 2024)

DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. - Yilun Xu; Gabriele Corso; Tommi S. Jaakkola; Arash Vahdat; Karsten Kreis (ICML, 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)

Composing Unbalanced Flows for Flexible Docking and Relaxation. - Gabriele Corso; Vignesh Ram Somnath; Noah Getz; Regina Barzilay; Tommi S. Jaakkola; Andreas Krause 001 (ICLR, 2025)