Dominique Beaini
Dominique Beaini
Machine Learning Researcher, InVivo AI
Verified email at
Cited by
Cited by
Principal neighbourhood aggregation for graph nets
G Corso, L Cavalleri, D Beaini, P Liò, P Veličković
NeurIPS2020, 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
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
Directional graph networks
D Beaini, S Passaro, V Létourneau, W Hamilton, G Corso, P Liò
International Conference on Machine Learning, 748-758, 2021
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
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
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
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
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
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
Deep green function convolution for improving saliency in convolutional neural networks
D Beaini, S Achiche, A Duperré, M Raison
The Visual Computer 37, 227-244, 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
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
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
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
Improving Convolutional Neural Networks Via Conservative Field Regularisation and Integration
D Beaini, S Achiche, M Raison
arXiv preprint arXiv:2003.05182, 2020
Object analysis in images using electric potentials and electric fields
D Beaini, M Raison, S Achiche
US Patent App. 16/331,208, 2019
Generating QM1B with PySCF
A Mathiasen, H Helal, K Klaser, P Balanca, J Dean, C Luschi, D Beaini, ...
arXiv preprint arXiv:2311.01135, 2023
Saliency Enhancement using Gradient Domain Edges Merging
D Beaini, S Achiche, A Duperre, M Raison
arXiv preprint arXiv:2002.04380, 2020
Fast and optimal Laplacian solver for gradient-domain image editing using Green function convolution
D Beaini, S Achiche, F Nonez, OB Dufour, C Leblond-Ménard, M Asaadi, ...
arXiv preprint arXiv:1902.00176, 2019
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