Prudencio Tossou

According to our database, Prudencio Tossou authored at least 13 papers between 2019 and 2024.

Collaborative distances:

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

2024

Real-World Molecular Out-Of-Distribution: Specification and Investigation.

Prudencio Tossou, Cas Wognum, Michael Craig, Hadrien Mary, Emmanuel Noutahi

J. Chem. Inf. Model., 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, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Role of Structural and Conformational Diversity for Machine Learning Potentials.

Nikhil Shenoy, Prudencio Tossou, Emmanuel Noutahi, Hadrien Mary, Dominique Beaini, Jiarui Ding

CoRR, 2023

Gotta be SAFE: A New Framework for Molecular Design.

Emmanuel Noutahi, Cristian Gabellini, Michael Craig, Jonathan S. C. Lim, Prudencio Tossou

CoRR, 2023

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, 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

CoRR, 2023

MOT: A Multi-Omics Transformer for Multiclass Classification Tumour Types Predictions.

Mazid Abiodoun Osseni, Prudencio Tossou, François Laviolette, Jacques Corbeil

Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023

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

2021

On the robustness of generalization of drug-drug interaction models.

Rogia Kpanou, Mazid Abiodoun Osseni, Prudencio Tossou, François Laviolette, Jacques Corbeil

BMC Bioinform., 2021

Rethinking Graph Transformers with Spectral Attention.

Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou

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

Applying PySCMGroup to Breast Cancer Biomarkers Discovery.

Mazid Abiodoun Osseni, Prudencio Tossou, Jacques Corbeil, François Laviolette

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021

2020

Geodesics in fibered latent spaces: A geometric approach to learning correspondences between conditions.

Tariq Daouda, Reda Chhaibi, Prudencio Tossou, Alexandra-Chloé Villani

CoRR, 2020

2019

Adaptive Deep Kernel Learning.

Prudencio Tossou, Basile Dura, François Laviolette, Mario Marchand, Alexandre Lacoste

CoRR, 2019

Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling.

Emmanuel Noutahi, Dominique Beaini, Julien Horwood, Prudencio Tossou

CoRR, 2019