Olivier Peltre

According to our database, Olivier Peltre authored at least 10 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Force-Aware Neural Tangent Kernels for Scalable and Robust Active Learning of MLIPs.

Eszter Varga-Umbrich, Zachary Weller-Davies, Paul Duckworth, Jules Tilly, Olivier Peltre, Shikha Surana

CoRR, May, 2026

Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs.

Eszter Varga-Umbrich, Shikha Surana, Paul Duckworth, Jules Tilly, Olivier Peltre, Zachary Weller-Davies

CoRR, May, 2026

2025

Universally applicable and tunable graph-based coarse-graining for Machine learning force fields.

Christoph Brunken, Sebastien Boyer, Mustafa Omar, Martin Maarand, Olivier Peltre, Solal Attias, Bakary N'tji Diallo, Anastasia Markina, Olaf Othersen, Oliver Bent

CoRR, April, 2025

2023

Local Max-Entropy and Free Energy Principles, Belief Diffusions and their Singularities.

Olivier Peltre

CoRR, 2023

Equivariant Message Passing Neural Network for Crystal Material Discovery.

Astrid Klipfel, Zied Bouraoui, Olivier Peltre, Yaël Frégier, Najwa Harrati, Adlane Sayede

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Local Max-Entropy and Free Energy Principles Solved by Belief Propagation.

Olivier Peltre

CoRR, 2022

2021

Belief Propagation as Diffusion.

Olivier Peltre

Proceedings of the Geometric Science of Information - 5th International Conference, 2021

2020

Geomstats: A Python Package for Riemannian Geometry in Machine Learning.

Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

CoRR, 2020

Introduction to Geometric Learning in Python with Geomstats.

Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

Proceedings of the 19th Python in Science Conference, 2020

2019

A Homological Approach to Belief Propagation and Bethe Approximations.

Olivier Peltre

Proceedings of the Geometric Science of Information - 4th International Conference, 2019