5 papers · 1 filter
Multi-Task Learning of Conditional Mean Operators: applications to dynamical systems and uncertainty quantification
Sami Chemlal, Thibaut Germain, Rémi Flamary +2
Estimating conditional statistics and learning representations of a population of conditional distributions are central problems in many data-driven applications, including uncerta…
Geometric Dictionary Learning of Dynamical Systems with Optimal Transport
Thibaut Germain, Sami Chemlal, Rémi Flamary +2
Learning dynamical systems through operator-theoretic representations provides a powerful framework for analyzing complex dynamics, as spectral quantities such as eigenvalues and i…
Outcome-Aware Spectral Feature Learning for Instrumental Variable Regression
Dimitri Meunier, Jakub Wornbard, Vladimir R. Kostic +5
We address the problem of causal effect estimation in the presence of hidden confounders using nonparametric instrumental variable (IV) regression. An established approach is to us…
A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems
Thibaut Germain, Rémi Flamary, Vladimir R. Kostic +1
The geometry of dynamical systems estimated from trajectory data is a major challenge for machine learning applications. Koopman and transfer operators provide a linear representat…
Demystifying Spectral Feature Learning for Instrumental Variable Regression
Dimitri Meunier, Antoine Moulin, Jakub Wornbard +2
We address the problem of causal effect estimation in the presence of hidden confounders, using nonparametric instrumental variable (IV) regression. A leading strategy employs spec…