Dominique Beaini

46 papers A* 13Journal 32Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Amortized Sampling with Transferable Normalizing Flows. CoRR Charlie B. Tan, Majdi Hassan, Leon Klein, Saifuddin Syed, Dominique Beaini, Michael M. Bronstein, Alexander Tong, Kirill Neklyudov
2025	J	`jnl`	Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities. CoRR Tara Akhound-Sadegh, Jungyoon Lee, Avishek Joey Bose, Valentin De Bortoli, Arnaud Doucet, Michael M. Bronstein, Dominique Beaini, Siamak Ravanbakhsh, Kirill Neklyudov, Alexander Tong
2025	J	`jnl`	Self-Refining Training for Amortized Density Functional Theory. CoRR Majdi Hassan, Cristian Gabellini, Hatem Helal, Dominique Beaini, Kirill Neklyudov
2025	J	`jnl`	Virtual Cells: Predict, Explain, Discover. CoRR Emmanuel Noutahi, Jason S. Hartford, Prudencio Tossou, Shawn Whitfield, Alisandra Kaye Denton, Cas Wognum, Kristina Ulicna, Michael Craig, Jonathan Hsu, Michael Cuccarese, Emmanuel Bengio, Dominique Beaini, Christopher Gibson, Daniel Cohen, Berton Earnshaw
2024	A*	`conf`	ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation. NeurIPS Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini
2024	J	`jnl`	ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation. CoRR Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stärk, Stephan Thaler, Dominique Beaini
2024	A*	`conf`	Graph Positional and Structural Encoder. ICML Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek
2024	A*	`conf`	How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval. NeurIPS Philip Fradkin, Puria Azadi Moghadam, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini
2024	J	`jnl`	How Molecules Impact Cells: Unlocking Contrastive PhenoMolecular Retrieval. CoRR Philip Fradkin, Puria Azadi, Karush Suri, Frederik Wenkel, Ali Bashashati, Maciej Sypetkowski, Dominique Beaini
2024	A*	`conf`	Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology. CVPR 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
2024	J	`jnl`	Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology. CoRR 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
2024	A*	`conf`	On the Scalability of GNNs for Molecular Graphs. NeurIPS Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini
2024	J	`jnl`	On the Scalability of GNNs for Molecular Graphs. CoRR Maciej Sypetkowski, Frederik Wenkel, Farimah Poursafaei, Nia Dickson, Karush Suri, Philip Fradkin, Dominique Beaini
2024	J	`jnl`	OpenQDC: Open Quantum Data Commons. CoRR Cristian Gabellini, Nikhil Shenoy, Stephan Thaler, Semih Cantürk, Daniel McNeela, Dominique Beaini, Michael M. Bronstein, Prudencio Tossou
2024	A*	`conf`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. ICLR 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, Michal 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
2023	J	`jnl`	GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. CoRR Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini
2023	J	`jnl`	GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. Trans. Mach. Learn. Res. Dominic Masters, Josef Dean, Kerstin Kläser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W. Fitzgibbon, Shenyang Huang, Ladislav Rampásek, Dominique Beaini
2023	A*	`conf`	Generating QM1B with PySCF NeurIPS Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters
2023	J	`jnl`	Generating QM1B with PySCF CoRR Alexander Mathiasen, Hatem Helal, Kerstin Klaser, Paul Balanca, Josef Dean, Carlo Luschi, Dominique Beaini, Andrew W. Fitzgibbon, Dominic Masters
2023	J	`jnl`	Graph Positional and Structural Encoder. CoRR Renming Liu, Semih Cantürk, Olivier Lapointe-Gagné, Vincent Létourneau, Guy Wolf, Dominique Beaini, Ladislav Rampásek
2023	J	`jnl`	Role of Structural and Conformational Diversity for Machine Learning Potentials. CoRR Nikhil Shenoy, Prudencio Tossou, Emmanuel Noutahi, Hadrien Mary, Dominique Beaini, Jiarui Ding
2023	J	`jnl`	Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao
2023	—	`conf`	The Second Learning on Graphs Conference: Preface. LoG 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
2023	J	`jnl`	Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. CoRR 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, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters
2022	A*	`conf`	3D Infomax improves GNNs for Molecular Property Prediction. ICML Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió
2022	J	`jnl`	GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction. CoRR Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini
2022	A*	`conf`	Long Range Graph Benchmark. NeurIPS Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
2022	J	`jnl`	Long Range Graph Benchmark. CoRR Vijay Prakash Dwivedi, Ladislav Rampásek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini
2022	A*	`conf`	Recipe for a General, Powerful, Scalable Graph Transformer. NeurIPS Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
2022	J	`jnl`	Recipe for a General, Powerful, Scalable Graph Transformer. CoRR Ladislav Rampásek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini
2021	J	`jnl`	3D Infomax improves GNNs for Molecular Property Prediction. CoRR Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Liò
2021	J	`jnl`	Deep green function convolution for improving saliency in convolutional neural networks. Vis. Comput. Dominique Beaini, Sofiane Achiche, Alexandre Duperré, Maxime Raison
2021	A*	`conf`	Directional Graph Networks. ICML Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió
2021	A*	`conf`	Rethinking Graph Transformers with Spectral Attention. NeurIPS Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
2021	J	`jnl`	Rethinking Graph Transformers with Spectral Attention. CoRR Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
2020	J	`jnl`	Directional Graph Networks. CoRR Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò
2020	J	`jnl`	Improving Convolutional Neural Networks Via Conservative Field Regularisation and Integration. CoRR Dominique Beaini, Sofiane Achiche, Maxime Raison
2020	A*	`conf`	Principal Neighbourhood Aggregation for Graph Nets. NeurIPS Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic
2020	J	`jnl`	Principal Neighbourhood Aggregation for Graph Nets. CoRR Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic
2020	J	`jnl`	Saliency Enhancement using Gradient Domain Edges Merging. CoRR Dominique Beaini, Sofiane Achiche, Alexandre Duperré, Maxime Raison
2019	J	`jnl`	Deep Green Function Convolution for Improving Saliency in Convolutional Neural Networks. CoRR Dominique Beaini, Sofiane Achiche, Alexandre Duperré, Maxime Raison
2019	J	`jnl`	Fast and Optimal Laplacian Solver for Gradient-Domain Image Editing using Green Function Convolution. CoRR Dominique Beaini, Sofiane Achiche, Fabrice Nonez, Olivier Brochu Dufour, Cédric Leblond-Ménard, Mahdis Asaadi, Maxime Raison
2019	J	`jnl`	Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling. CoRR Emmanuel Noutahi, Dominique Beaini, Julien Horwood, Prudencio Tossou
2018	J	`jnl`	Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications. CoRR Dominique Beaini, Sofiane Achiche, Fabrice Nonez, Maxime Raison
2018	J	`jnl`	Novel Convolution Kernels for Computer Vision and Shape Analysis based on Electromagnetism. CoRR Dominique Beaini, Sofiane Achiche, Yann-Seing Law-Kam Cio, Maxime Raison
2017	J	`jnl`	Fast scene analysis using vision and artificial intelligence for object prehension by an assistive robot. Eng. Appl. Artif. Intell. C. Bousquet-Jette, Sofiane Achiche, Dominique Beaini, Y. S. Law-Kam Cio, Cédric Leblond-Ménard, Maxime Raison