8 papers
Geometry-Aware Decentralized Sinkhorn for Wasserstein Barycenters
Ali Baheri, Alireza Vahid
Distributed systems require fusing heterogeneous local probability distributions into a global summary over sparse and unreliable communication networks. Traditional consensus algo…
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…
Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting
Carlos A. Pereira, Stéphane Gaudreault, Valentin Dallerit +9
Recent machine-learning approaches to weather forecasting often employ a monolithic architecture in which distinct physical mechanisms-advection (long-range transport), diffusion-l…
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…
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…
Split Conformal Prediction in the Function Space with Neural Operators
David Millard, Lars Lindemann, Ali Baheri
Uncertainty quantification for neural operators remains an open problem in the infinite-dimensional setting due to the lack of finite-sample coverage guarantees over functional out…