2 papers
stat.ML2020
Geodesics in fibered latent spaces: A geometric approach to learning correspondences between conditions
Tariq Daouda, Reda Chhaibi, Prudencio Tossou +1
This work introduces a geometric framework and a novel network architecture for creating correspondences between samples of different conditions. Under this formalism, the latent s…
stat.ML2018
Holographic Neural Architectures
Tariq Daouda, Jeremie Zumer, Claude Perreault +1
Representation learning is at the heart of what makes deep learning effective. In this work, we introduce a new framework for representation learning that we call "Holographic Neur…