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ORCIDAlexandre Duval
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2020 – today
- 2024
[j1]Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick:
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design. J. Mach. Learn. Res. 25: 106:1-106:26 (2024)- [i10]Ali Ramlaoui, Théo Saulus, Basile Terver, Victor Schmidt, David Rolnick, Fragkiskos D. Malliaros, Alexandre Duval:
Improving Molecular Modeling with Geometric GNNs: an Empirical Study. CoRR abs/2407.08313 (2024) - 2023
- [c7]Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick:
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. ICML 2023: 9013-9033 - [c6]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:
The Second Learning on Graphs Conference: Preface. LoG 2023: i-xix - [c5]Alexandre Duval, Anita Paas, Abdalwhab Abdalwhab, David St-Onge:
The eyes and hearts of UAV pilots: observations of physiological responses in real-life scenarios. RO-MAN 2023: 2352-2358 - [i9]Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick:
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. CoRR abs/2305.05577 (2023) - [i8]Alex Hernández-García, Alexandre Duval, Alexandra Volokhova, Yoshua Bengio, Divya Sharma, Pierre Luc Carrier, Michal Koziarski, Victor Schmidt:
Crystal-GFN: sampling crystals with desirable properties and constraints. CoRR abs/2310.04925 (2023) - [i7]Alvaro Carbonero, Alexandre Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick:
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions. CoRR abs/2310.06682 (2023) - [i6]Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein:
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR abs/2312.07511 (2023) - 2022
- [c4]Alexandre Duval
, Fragkiskos D. Malliaros:
Higher-order Clustering and Pooling for Graph Neural Networks. CIKM 2022: 426-435 - [i5]Alexandre Duval, Fragkiskos D. Malliaros:
Higher-order Clustering and Pooling for Graph Neural Networks. CoRR abs/2209.03473 (2022) - [i4]Alexandre Duval, Anita Paas, Abdalwhab Abdalwhab, David St-Onge:
The eyes and hearts of UAV pilots: observations of physiological responses in real-life scenarios. CoRR abs/2210.14910 (2022) - [i3]Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick:
PhAST: Physics-Aware, Scalable, and Task-specific GNNs for Accelerated Catalyst Design. CoRR abs/2211.12020 (2022) - 2021
- [c3]Alexandre Duval, Thomas Lamson, Gael de Leseleuc de Kerouara, Matthias Gallé:
Breaking Writer's Block: Low-cost Fine-tuning of Natural Language Generation Models. EACL (System Demonstrations) 2021: 278-287 - [c2]Alexandre Duval, Fragkiskos D. Malliaros:
GraphSVX: Shapley Value Explanations for Graph Neural Networks. ECML/PKDD (2) 2021: 302-318 - [i2]Alexandre Duval, Gael de Leseleuc de Kerouara, Thomas Lamson:
Controllable and contextualised writing tool for novel authors. CoRR abs/2101.03216 (2021) - [i1]Alexandre Duval, Fragkiskos D. Malliaros:
GraphSVX: Shapley Value Explanations for Graph Neural Networks. CoRR abs/2104.10482 (2021) - 2020
- [c1]Nora S. Newcombe, Alexandre Duval, Sang Ah Lee, Anna Shusterman, Noam Miller:
Getting Our Bearings: Advances in Understanding Spatial Reorientation. CogSci 2020
Coauthor Index
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