David Millard

According to our database, David Millard authored at least 9 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Federated Distributional Reinforcement Learning with Distributional Critic Regularization.

David Millard, Cecilia O. Alm, Rashid Ali, Pengcheng Shi, Ali Baheri

CoRR, March, 2026

Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting.

Carlos A. Pereira, Stéphane Gaudreault, Valentin Dallerit, Christopher Subich, Shoyon Panday, Siqi Wei, Sasa Zhang, Siddharth Rout, Eldad Haber, Raymond J. Spiteri, David Millard, Emilia Diaconescu

CoRR, January, 2026

Can Optimal Transport Improve Federated Inverse Reinforcement Learning?

David Millard, Ali Baheri

CoRR, January, 2026

2025

Geometry-Aware Decentralized Sinkhorn for Wasserstein Barycenters.

Ali Baheri, David Millard, Alireza Vahid

CoRR, September, 2025

Split Conformal Prediction in the Function Space with Neural Operators.

David Millard, Lars Lindemann, Ali Baheri

CoRR, September, 2025

DEF: Diffusion-augmented Ensemble Forecasting.

David Millard, Arielle Carr, Stéphane Gaudreault, Ali Baheri

CoRR, June, 2025

PEARL: Preconditioner Enhancement through Actor-critic Reinforcement Learning.

David Millard, Arielle Carr, Stéphane Gaudreault, Ali Baheri

CoRR, January, 2025

2024

Data-Driven Initial Guess Selection for Numerical Weather Prediction Solvers.

David Millard, Arielle Carr, Stéphane Gaudreault

Proceedings of the IEEE International Conference on Big Data, 2024

Deep Learning for Koopman Operator Estimation in Idealized Atmospheric Dynamics.

David Millard, Arielle Carr, Stéphane Gaudreault

Proceedings of the IEEE International Conference on Big Data, 2024