Papers

On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory
Andrea Perin, Stéphane Deny
JMLR 2025
[PDF][arXiv]

ViewFusion: Learning Composable Diffusion Models for Novel View Synthesis
Bernard Spiegl, Andrea Perin, Stéphane Deny, Alexander Ilin
TMLR 2025
[PDF][arXiv]

A comparison between humans and AI at recognizing objects in unusual poses
Netta Ollikka, Amro Abbas, Andrea Perin, Markku Kilpeläinen, Stéphane Deny
TMLR 2025
[PDF][arXiv]

Blockwise Self-Supervised Learning at Scale
Shoaib Ahmed Siddiqui, David Krueger, Yann LeCun, Stéphane Deny
TMLR 2024
[PDF][arXiv]

Progress and limitations of deep networks to recognize objects in unusual poses
Amro Abbas, Stéphane Deny
AAAI 2023
[PDF][arXiv]

On the special role of class-selective neurons in early training
Omkar Ranadive, Nikhil Thakurdesai, Ari S Morcos, Matthew Leavitt, Stéphane Deny
TMLR 2023
[PDF][arXiv]

Preprints

A Deep Learning Model of Mental Rotation Informed by Interactive VR Experiments
Raymond Khazoum, Daniela Fernandes, Aleksandr Krylov, Qin Li, Stéphane Deny
arXiv 2025
[PDF][arXiv]