Beaini, Dominique

31 publications

NeurIPS 2025 Amortized Sampling with Transferable Normalizing Flows Charlie B. Tan, Majdi Hassan, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong, Kirill Neklyudov

NeurIPS 2025 Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities Tara Akhound-Sadegh, Jungyoon Lee, Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong

ICLRW 2025 Scaling Deep Learning Solutions for Transition Path Sampling Jungyoon Lee, Michael Plainer, Yuanqi Du, Lars Holdijk, Rob Brekelmans, Dominique Beaini, Kirill Neklyudov

ICLRW 2025 Scaling Deep Learning Solutions for Transition Path Sampling Jungyoon Lee, Michael Plainer, Yuanqi Du, Lars Holdijk, Rob Brekelmans, Carla P Gomes, Dominique Beaini, Kirill Neklyudov

NeurIPS 2024 ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini

ICMLW 2024 Equivariant Flow Matching for Molecular Conformer Generation Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stark, Stephan Thaler, Dominique Beaini

ICMLW 2024 Equivariant Flow Matching for Molecular Conformer Generation Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stark, Stephan Thaler, Dominique Beaini

ICML 2024 Graph Positional and Structural Encoder Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampášek

NeurIPS 2024 How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval Philip Fradkin, Puria Azadi, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini

CVPR 2024 Masked Autoencoders for Microscopy Are Scalable Learners of Cellular Biology Oren Kraus, Kian Kenyon-Dean, Saber Saberian, Maryam Fallah, Peter McLean, Jess Leung, Vasudev Sharma, Ayla Khan, Jia Balakrishnan, Safiye Celik, Dominique Beaini, Maciej Sypetkowski, Chi Vicky Cheng, Kristen Morse, Maureen Makes, Ben Mabey, Berton Earnshaw

NeurIPSW 2024 Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini

NeurIPSW 2024 Molphenix: A Multimodal Foundation Model for PhenoMolecular Retrieval Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Maciej Sypetkowski, Dominique Beaini

NeurIPS 2024 On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

ICLRW 2024 On the Scalability of GNNs for Molecular Graphs Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini

ICLR 2024 Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

TMLR 2023 GPS++: Reviving the Art of Message Passing for Molecular Property Prediction Dominic Masters, Josef Dean, Kerstin Klaeser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W Fitzgibbon, Shenyang Huang, Ladislav Rampášek, Dominique Beaini

NeurIPS 2023 Generating QM1B with PySCF$_{\text{IPU}}$ Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters

NeurIPSW 2023 Latent Space Simulator for Unveiling Molecular Free Energy Landscapes and Predicting Transition Dynamics Simon Dobers, Hannes Stark, Xiang Fu, Dominique Beaini, Stephan Günnemann

ICMLW 2023 Repurposing Density Functional Theory to Suit Deep Learning Alexander Mathiasen, Hatem Helal, Paul Balanca, Kerstin Klaeser, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W Fitzgibbon, Dominic Masters

NeurIPSW 2023 Role of Structural and Conformational Diversity for Machine Learning Potentials Nikhil Shenoy, Prudencio Tossou, Emmanuel Noutahi, Hadrien Mary, Dominique Beaini, Jiarui Ding

NeurIPSW 2023 Role of Structural and Conformational Diversity for Machine Learning Potentials Nikhil Shenoy, Prudencio Tossou, Emmanuel Noutahi, Hadrien Mary, Dominique Beaini, Jiarui Ding

ICLRW 2023 Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Yiren Zhao, Pietro Lio

LoG 2023 The Second Learning on Graphs Conference: Preface Soledad Villar, Benjamin Chamberlain, Yuanqi Du, Hannes St"ark, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan

ICML 2022 3D Infomax Improves GNNs for Molecular Property Prediction Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió

NeurIPS 2022 Long Range Graph Benchmark Vijay Prakash Dwivedi, Ladislav Rampášek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

NeurIPS 2022 Recipe for a General, Powerful, Scalable Graph Transformer Ladislav Rampášek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

NeurIPSW 2021 3D Infomax Improves GNNs for Molecular Property Prediction Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lio

ICML 2021 Directional Graph Networks Dominique Beaini, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso, Pietro Lió

ICLRW 2021 Directional Graph Networks Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò

NeurIPS 2021 Rethinking Graph Transformers with Spectral Attention Devin Kreuzer, Dominique Beaini, Will Hamilton, Vincent Létourneau, Prudencio Tossou

NeurIPS 2020 Principal Neighbourhood Aggregation for Graph Nets Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Veličković