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2020 – today
- 2023
[i16]Xiangyu Zhao, Hannes Stärk, Dominique Beaini, Pietro Liò, Yiren Zhao:
Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. CoRR abs/2301.11517 (2023)- [i15]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:
GPS++: Reviving the Art of Message Passing for Molecular Property Prediction. CoRR abs/2302.02947 (2023) - 2022
- [c6]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Lió:
3D Infomax improves GNNs for Molecular Property Prediction. ICML 2022: 20479-20502 - [c5]Vijay Prakash Dwivedi, Ladislav Rampásek, Michael Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. NeurIPS 2022 - [c4]Ladislav Rampásek, Michael Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. NeurIPS 2022 - [i14]Ladislav Rampásek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini:
Recipe for a General, Powerful, Scalable Graph Transformer. CoRR abs/2205.12454 (2022) - [i13]Vijay Prakash Dwivedi, Ladislav Rampásek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini:
Long Range Graph Benchmark. CoRR abs/2206.08164 (2022) - [i12]Dominic Masters, Josef Dean, Kerstin Klaser, Zhiyi Li, Sam Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Ladislav Rampásek, Dominique Beaini:
GPS++: An Optimised Hybrid MPNN/Transformer for Molecular Property Prediction. CoRR abs/2212.02229 (2022) - 2021
- [j2]Dominique Beaini
, Sofiane Achiche, Alexandre Duperré, Maxime Raison:
Deep green function convolution for improving saliency in convolutional neural networks. Vis. Comput. 37(2): 227-244 (2021) - [c3]Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Lió:
Directional Graph Networks. ICML 2021: 748-758 - [c2]Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou:
Rethinking Graph Transformers with Spectral Attention. NeurIPS 2021: 21618-21629 - [i11]Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou:
Rethinking Graph Transformers with Spectral Attention. CoRR abs/2106.03893 (2021) - [i10]Hannes Stärk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan Günnemann, Pietro Liò:
3D Infomax improves GNNs for Molecular Property Prediction. CoRR abs/2110.04126 (2021) - 2020
- [c1]Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic:
Principal Neighbourhood Aggregation for Graph Nets. NeurIPS 2020 - [i9]Dominique Beaini, Sofiane Achiche, Alexandre Duperré, Maxime Raison:
Saliency Enhancement using Gradient Domain Edges Merging. CoRR abs/2002.04380 (2020) - [i8]Dominique Beaini, Sofiane Achiche, Maxime Raison:
Improving Convolutional Neural Networks Via Conservative Field Regularisation and Integration. CoRR abs/2003.05182 (2020) - [i7]Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Velickovic:
Principal Neighbourhood Aggregation for Graph Nets. CoRR abs/2004.05718 (2020) - [i6]Dominique Beaini, Saro Passaro, Vincent Létourneau, William L. Hamilton, Gabriele Corso, Pietro Liò:
Directional Graph Networks. CoRR abs/2010.02863 (2020)
2010 – 2019
- 2019
- [i5]Dominique Beaini, Sofiane Achiche, Fabrice Nonez, Olivier Brochu Dufour, Cédric Leblond-Ménard, Mahdis Asaadi, Maxime Raison:
Fast and Optimal Laplacian Solver for Gradient-Domain Image Editing using Green Function Convolution. CoRR abs/1902.00176 (2019) - [i4]Emmanuel Noutahi, Dominique Beaini, Julien Horwood, Prudencio Tossou:
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling. CoRR abs/1905.11577 (2019) - [i3]Dominique Beaini, Sofiane Achiche, Alexandre Duperré, Maxime Raison:
Deep Green Function Convolution for Improving Saliency in Convolutional Neural Networks. CoRR abs/1908.08331 (2019) - 2018
- [i2]Dominique Beaini, Sofiane Achiche, Fabrice Nonez, Maxime Raison:
Computing the Spatial Probability of Inclusion inside Partial Contours for Computer Vision Applications. CoRR abs/1806.01339 (2018) - [i1]Dominique Beaini, Sofiane Achiche, Yann-Seing Law-Kam Cio, Maxime Raison:
Novel Convolution Kernels for Computer Vision and Shape Analysis based on Electromagnetism. CoRR abs/1806.07996 (2018) - 2017
- [j1]C. Bousquet-Jette, Sofiane Achiche, Dominique Beaini, Y. S. Law-Kam Cio, Cédric Leblond-Ménard, Maxime Raison:
Fast scene analysis using vision and artificial intelligence for object prehension by an assistive robot. Eng. Appl. Artif. Intell. 63: 33-44 (2017)
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last updated on 2023-05-13 04:03 CEST by the dblp team
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