2026
Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
Julien Lalanne, David Picard, Lionel Boillot, Lina-María GUAYACÁN-CARRILLO, Leon Barens, Jean-Michel Pereira
ICML 2026poster
Generative modeling provides a powerful framework for learning data distributions. These models initially relied on probabilistic methods such as Gaussian Processes (GP) for uncertainty-aware predictions and shifted towards larger trainable models to learn more complex distributions. In this work, w…