54 citations · 227 across the 36 of their papers we have counts for
4 papers · 1 filter
Distribution-Based Invariant Deep Networks for Learning Meta-Features
Gwendoline De Bie, Herilalaina Rakotoarison, Gabriel Peyré +1
Recent advances in deep learning from probability distributions successfully achieve classification or regression from distribution samples, thus invariant under permutation of the…
Variational Auto-Encoder: not all failures are equal
Michele Sebag, Victor Berger, Michèle Sebag
We claim that a source of severe failures for Variational Auto-Encoders is the choice of the distribution class used for the observation model.A first theoretical and experimental…
Cartolabe: A Web-Based Scalable Visualization of Large Document Collections
Caillou Philippe, Renault Jonas, Fekete Jean-Daniel +2
We describe CARTOLABE, a web-based multi-scale system for visualizing and exploring large textual corpora based on topics, introducing a novel mechanism for the progressive visuali…
From abstract items to latent spaces to observed data and back: Compositional Variational Auto-Encoder
Victor Berger, Michèle Sebag
Conditional Generative Models are now acknowledged an essential tool in Machine Learning. This paper focuses on their control. While many approaches aim at disentangling the data t…