Alexandre Duval

According to our database, Alexandre Duval authored at least 19 papers between 2020 and 2026.

Collaborative distances:

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

2026

EquiformerV3: Scaling Efficient, Expressive, and General SE(3)-Equivariant Graph Attention Transformers.

Yi-Lun Liao, Alexander J. Hoffman, Sabrina C. Shen, Alexandre Duval, Sam Walton Norwood, Tess E. Smidt

CoRR, April, 2026

2025

LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models.

Siddharth Betala, Samuel P. Gleason, Ali Ramlaoui, Andy Xu, Georgia Channing, Daniel Levy, Clémentine Fourrier, Nikita Kazeev, Chaitanya K. Joshi, Sékou-Oumar Kaba, Félix Therrien, Alex Hernández-García, Rocío Mercado, N. M. Anoop Krishnan, Alexandre Duval

CoRR, December, 2025

LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature.

Magdalena Lederbauer, Siddharth Betala, Xiyao Li, Ayush Jain, Amine Sehaba, Georgia Channing, Grégoire Germain, Anamaria Leonescu, Faris Flaifil, Alfonso Amayuelas, Alexandre Nozadze, Stefan P. Schmid, Mohd Zaki, Sudheesh Kumar Ethirajan, Elton Pan, Mathilde Franckel, Alexandre Duval, N. M. Anoop Krishnan, Samuel P. Gleason

CoRR, October, 2025

Catalyst GFlowNet for electrocatalyst design: A hydrogen evolution reaction case study.

Lena Podina, Christina Humer, Alexandre Duval, Victor Schmidt, Ali Ramlaoui, Shahana Chatterjee, Yoshua Bengio, Alex Hernández-García, David Rolnick, Félix Therrien

CoRR, October, 2025

LeMat-Traj: A Scalable and Unified Dataset of Materials Trajectories for Atomistic Modeling.

Ali Ramlaoui, Martin Siron, Inel Djafar, Joseph Musielewicz, Amandine Rossello, Victor Schmidt, Alexandre Duval

CoRR, August, 2025

2024

A Graph Machine Learning Journey: from Explainability to Climate Action. (Apprentissage Automatique sur Graphes: de l'Explicabilité à l'Action Climatique).

Alexandre Duval

PhD thesis, 2024

PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design.

Alexandre Duval, Victor Schmidt, Santiago Miret, Yoshua Bengio, Alex Hernández-García, David Rolnick

J. Mach. Learn. Res., 2024

Improving Molecular Modeling with Geometric GNNs: an Empirical Study.

Ali Ramlaoui, Théo Saulus, Basile Terver, Victor Schmidt, David Rolnick, Fragkiskos D. Malliaros, Alexandre Duval

CoRR, 2024

2023

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.

Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein

CoRR, 2023

On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions.

Alvaro Carbonero, Alexandre Duval, Victor Schmidt, Santiago Miret, Alex Hernández-García, Yoshua Bengio, David Rolnick

CoRR, 2023

Crystal-GFN: sampling crystals with desirable properties and constraints.

Alex Hernández-García, Alexandre Duval, Alexandra Volokhova, Yoshua Bengio, Divya Sharma, Pierre Luc Carrier, Michal Koziarski, Victor Schmidt

CoRR, 2023

The eyes and hearts of UAV pilots: observations of physiological responses in real-life scenarios.

Alexandre Duval, Anita Paas, Abdalwhab Abdalwhab, David St-Onge

Proceedings of the 32nd IEEE International Conference on Robot and Human Interactive Communication, 2023

The Second Learning on Graphs Conference: Preface.

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

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

FAENet: Frame Averaging Equivariant GNN for Materials Modeling.

Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick

Proceedings of the International Conference on Machine Learning, 2023

2022

Higher-order Clustering and Pooling for Graph Neural Networks.

Alexandre Duval, Fragkiskos D. Malliaros

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Controllable and contextualised writing tool for novel authors.

Alexandre Duval, Gael de Leseleuc de Kerouara, Thomas Lamson

CoRR, 2021

GraphSVX: Shapley Value Explanations for Graph Neural Networks.

Alexandre Duval, Fragkiskos D. Malliaros

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Breaking Writer's Block: Low-cost Fine-tuning of Natural Language Generation Models.

Alexandre Duval, Thomas Lamson, Gael de Leseleuc de Kerouara, Matthias Gallé

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, 2021

2020

Getting Our Bearings: Advances in Understanding Spatial Reorientation.

Nora S. Newcombe, Alexandre Duval, Sang Ah Lee, Anna Shusterman, Noam Miller

Proceedings of the 42th Annual Meeting of the Cognitive Science Society, 2020