1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
One-Step Voice Conversion by Learning kNN Transport in WavLM Space
Anton Selitskiy, David Millard
Voice conversion (VC) systems fall into two families: non-parametric embedding-space methods, which need no trained model but degrade on short target utterances, and spectrogram-ba…
Stability of the Monge Map in Semi-Dual Optimal Transport
Anton Selitskiy, David Millard
This paper shows that the semi-dual formulation of the optimal transport problem has a degenerate saddle-point structure, and that its numerical solution is equivalent to solving a…
Federated Distributional Reinforcement Learning with Distributional Critic Regularization
David Millard, Cecilia Alm, Rashid Ali +2
Federated reinforcement learning typically aggregates value functions or policies by parameter averaging, which emphasizes expected return and can obscure statistical multimodality…
Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting
Carlos A. Pereira, Stéphane Gaudreault, Valentin Dallerit +9
Machine-learning approaches to weather forecasting often employ a monolithic architecture in which distinct physical mechanisms, such as advection, diffusive mixing, thermodynamic…
Can Optimal Transport Improve Federated Inverse Reinforcement Learning?
David Millard, Ali Baheri
In robotics and multi-agent systems, fleets of autonomous agents often operate in subtly different environments while pursuing a common high-level objective. Directly pooling their…