4 papers
Mixture of Raytraced Experts
Andrea Perin, Giacomo Lagomarsini, Claudio Gallicchio +1
We introduce a Mixture of Raytraced Experts, a stacked Mixture of Experts (MoE) architecture which can dynamically select sequences of experts, producing computational graphs of va…
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…
ViewFusion: Learning Composable Diffusion Models for Novel View Synthesis
Bernard Spiegl, Andrea Perin, Stéphane Deny +1
Deep learning is providing a wealth of new approaches to the problem of novel view synthesis, from Neural Radiance Field (NeRF) based approaches to end-to-end style architectures.…
A comparison between humans and AI at recognizing objects in unusual poses
Netta Ollikka, Amro Abbas, Andrea Perin +2
Deep learning is closing the gap with human vision on several object recognition benchmarks. Here we investigate this gap for challenging images where objects are seen in unusual p…