3 papers
cs.CV2026
Latent Equivariant Operators for Robust Object Recognition: Promises and Challenges
Minh Dinh, Stéphane Deny
Despite the successes of deep learning in computer vision, difficulties persist in recognizing objects that have undergone group-symmetric transformations rarely seen during traini…
q-bio.NC2025
A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments
Raymond Khazoum, Daniela Fernandes, Aleksandr Krylov +2
Mental rotation -- the ability to compare objects seen from different viewpoints -- is a fundamental example of mental simulation and spatial world modeling in humans. Here we prop…
cs.LG2024
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
Andrea Perin, Stephane Deny
Symmetries (transformations by group actions) are present in many datasets, and leveraging them holds considerable promise for improving predictions in machine learning. In this wo…