3 papers
cs.LG2025
Speeding Up MACE: Low-Precision Tricks for Equivarient Force Fields
Alexandre Benoit
Machine-learning force fields can deliver accurate molecular dynamics (MD) at high computational cost. For SO(3)-equivariant models such as MACE, there is little systematic evidenc…
cs.LG2025
Structural Invariance Matters: Rethinking Graph Rewiring through Graph Metrics
Alexandre Benoit, Catherine Aitken, Yu He
Graph rewiring has emerged as a key technique to alleviate over-squashing in Graph Neural Networks (GNNs) and Graph Transformers by modifying the graph topology to improve informat…
cs.CV2024
A Multitask Deep Learning Model for Classification and Regression of Hyperspectral Images: Application to the large-scale dataset
Koushikey Chhapariya, Alexandre Benoit, Krishna Mohan Buddhiraju +1
Multitask learning is a widely recognized technique in the field of computer vision and deep learning domain. However, it is still a research question in remote sensing, particular…