1 citations · 2 across the 4 of their papers we have counts for
4 papers
DEF: Diffusion-augmented Ensemble Forecasting
David Millard, Arielle Carr, Stéphane Gaudreault +1
We present DEF (\textbf{\ul{D}}iffusion-augmented \textbf{\ul{E}}nsemble \textbf{\ul{F}}orecasting), a novel approach for generating initial condition perturbations. Modern approac…
PEARL: Preconditioner Enhancement through Actor-critic Reinforcement Learning
David Millard, Arielle Carr, Stéphane Gaudreault +1
We present PEARL (Preconditioner Enhancement through Actor-critic Reinforcement Learning), a novel approach to learning matrix preconditioners. Existing preconditioners such as Jac…
Deep Learning for Koopman Operator Estimation in Idealized Atmospheric Dynamics
David Millard, Arielle Carr, Stéphane Gaudreault
Deep learning is revolutionizing weather forecasting, with new data-driven models achieving accuracy on par with operational physical models for medium-term predictions. However, t…
Challenges in computing matrix functions
Massimiliano Fasi, Stéphane Gaudreault, Kathryn Lund +1
This manuscript summarizes the outcome of the focus groups at "The f(A)bulous workshop on matrix functions and exponential integrators", held at the Max Planck Institute for Dynami…