Principal neighbourhood aggregation for graph nets G Corso, L Cavalleri, D Beaini, P Liò, P Veličković
NeurIPS2020, 2020
665 2020 Rethinking graph transformers with spectral attention D Kreuzer, D Beaini, W Hamilton, V Létourneau, P Tossou
Advances in Neural Information Processing Systems 34, 21618-21629, 2021
442 2021 Recipe for a general, powerful, scalable graph transformer L Rampášek, M Galkin, VP Dwivedi, AT Luu, G Wolf, D Beaini
Advances in Neural Information Processing Systems 35, 14501-14515, 2022
382 2022 3d infomax improves gnns for molecular property prediction H Stärk, D Beaini, G Corso, P Tossou, C Dallago, S Günnemann, P Liò
International Conference on Machine Learning, 20479-20502, 2022
189 2022 Directional graph networks D Beaini, S Passaro, V Létourneau, W Hamilton, G Corso, P Liò
International Conference on Machine Learning, 748-758, 2021
179 2021 Long range graph benchmark VP Dwivedi, L Rampášek, M Galkin, A Parviz, G Wolf, AT Luu, D Beaini
Advances in Neural Information Processing Systems 35, 22326-22340, 2022
158 2022 Fast scene analysis using vision and artificial intelligence for object prehension by an assistive robot C Bousquet-Jette, S Achiche, D Beaini, YSLK Cio, C Leblond-Ménard, ...
Engineering Applications of Artificial Intelligence 63, 33-44, 2017
45 2017 Towards interpretable sparse graph representation learning with laplacian pooling E Noutahi, D Beaini, J Horwood, S Giguère, P Tossou
arXiv preprint arXiv:1905.11577, 2019
38 2019 Image-based truss recognition for density-based topology optimization approach JF Gamache, A Vadean, É Noirot-Nérin, D Beaini, S Achiche
Structural and Multidisciplinary Optimization 58, 2697-2709, 2018
25 2018 Gps++: An optimised hybrid mpnn/transformer for molecular property prediction D Masters, J Dean, K Klaser, Z Li, S Maddrell-Mander, A Sanders, H Helal, ...
arXiv preprint arXiv:2212.02229, 2022
18 2022 Towards foundational models for molecular learning on large-scale multi-task datasets D Beaini, S Huang, JA Cunha, G Moisescu-Pareja, O Dymov, ...
arXiv preprint arXiv:2310.04292, 2023
12 2023 Deep green function convolution for improving saliency in convolutional neural networks D Beaini, S Achiche, A Duperré, M Raison
The Visual Computer 37 (2), 227-244, 2021
7 2021 Novel convolution kernels for computer vision and shape analysis based on electromagnetism D Beaini, S Achiche, YSLK Cio, M Raison
arXiv preprint arXiv:1806.07996, 2018
6 2018 Computing the spatial probability of inclusion inside partial contours for computer vision applications D Beaini, S Achiche, F Nonez, M Raison
arXiv preprint arXiv:1806.01339, 2018
6 2018 Design guidelines for shoulder design of an anthropomorphic robotic arm M Leroux, S Achiche, D Beaini, M Raison
DS 87-4 Proceedings of the 21st International Conference on Engineering …, 2017
5 2017 Generating QM1B with PySCF A Mathiasen, H Helal, K Klaser, P Balanca, J Dean, C Luschi, D Beaini, ...
Advances in Neural Information Processing Systems 36, 55036-55050, 2023
4 2023 Gps++: Reviving the art of message passing for molecular property prediction D Masters, J Dean, K Klaser, Z Li, S Maddrell-Mander, A Sanders, H Helal, ...
arXiv preprint arXiv:2302.02947, 2023
4 2023 Graph Positional and Structural Encoder R Liu, S Cantürk, O Lapointe-Gagné, V Létourneau, G Wolf, D Beaini, ...
arXiv preprint arXiv:2307.07107, 2023
3 2023 Improving Convolutional Neural Networks Via Conservative Field Regularisation and Integration D Beaini, S Achiche, M Raison
arXiv preprint arXiv:2003.05182, 2020
2 2020 Saliency Enhancement using Gradient Domain Edges Merging D Beaini, S Achiche, A Duperré, M Raison
arXiv preprint arXiv:2002.04380, 2020
2 2020 
