23 citations · 44 across the 8 of their papers we have counts for
10 papers
VolTeMorph: Realtime, Controllable and Generalisable Animation of Volumetric Representations
Stephan J. Garbin, Marek Kowalski, Virginia Estellers +5
The recent increase in popularity of volumetric representations for scene reconstruction and novel view synthesis has put renewed focus on animating volumetric content at high visu…
Offline Reinforcement Learning as Anti-Exploration
Shideh Rezaeifar, Robert Dadashi, Nino Vieillard +4
Offline Reinforcement Learning (RL) aims at learning an optimal control from a fixed dataset, without interactions with the system. An agent in this setting should avoid selecting…
Offline Reinforcement Learning with Pseudometric Learning
Robert Dadashi, Shideh Rezaeifar, Nino Vieillard +3
Offline Reinforcement Learning methods seek to learn a policy from logged transitions of an environment, without any interaction. In the presence of function approximation, and und…
Information bottleneck through variational glasses
Slava Voloshynovskiy, Mouad Kondah, Shideh Rezaeifar +3
Information bottleneck (IB) principle [1] has become an important element in information-theoretic analysis of deep models. Many state-of-the-art generative models of both Variatio…
-VAE: Autoregressive parametrization of the VAE encoder
Sohrab Ferdowsi, Maurits Diephuis, Shideh Rezaeifar +1
We make a minimal, but very effective alteration to the VAE model. This is about a drop-in replacement for the (sample-dependent) approximate posterior to change it from the standa…
Robustification of deep net classifiers by key based diversified aggregation with pre-filtering
Olga Taran, Shideh Rezaeifar, Taras Holotyak +1
In this paper, we address a problem of machine learning system vulnerability to adversarial attacks. We propose and investigate a Key based Diversified Aggregation (KDA) mechanism…