Poster presentation

February 17th, 17:10-18:30

1. Matthieu Darcy  Machine Learning for Solving Partial Differential Equations with Singular Forcing

2. Jonghyeon Lee  Learning Normal Forms with Kernel Methods

3. Pau Batlle Franch  Decision Theoretical Uncertainty Quantification for Dynamical Systems

4. Baige Xu  A Posteriori Error Estimation of Numerical Solutions of PINNs for the Navier-Stokes Equations

5. Gangnan Yuan  An Efficient Gaussian Mixture Model and Its Application to Neural Network

6. Florian Rossmannek  On state space systems and stochastic echo states

February 18th, 12:00-13:20

1. Isao Ishikawa  On finite-dimensional approximations of push-forwards on locally analytic functionals

2. James Murray Louw  Prediction of causal dynamics using universal reservoirs

3. Hannah Lim Jing Ting  Infinite-dimensional next-generation reservoir computing

4. Tomohisa Okazaki  Physics-Informed Learning of Earthquake Deformation

5. Satoshi Oishi  Reducing Redundancy in Reservoir Computing to Address Overembedding

6. Charles Riou  Fast Rates in Meta-Learning with PAC-Bayes

Titles and abstracts