Dear all, Join us for our upcoming talk in the SURE-AI<https://www.mn.uio.no/math/english/research/groups/risk-stochastics/star-seminar/> STAR seminar <https://www.mn.uio.no/math/english/research/groups/risk-stochastics/star-seminar/> series on Thursday, October 8th, from 11:15 to 12:00 (Oslo time). As always, the talk will take place in a hybrid format: participants in Oslo can attend the talk in Room 723 in Niels Henrik Abels hus, whereas the international audience will be able to follow the talk via Zoom<https://uio.zoom.us/j/64628994183>. The speaker is Sebastian Zeng (Linnæus University) with the talk: Title: Latent Variable Learning of SPDEs Abstract: We study the problem of learning the law of linear stochastic partial differential equations (SPDEs) with additive Gaussian forcing from spatiotemporal observations. Most existing approaches either assume access to the driving noise or initial condition, rely on deterministic surrogates that fail to capture intrinsic stochasticity, or employ generative models (e.g., diffusion models) that capture local randomness but may accumulate distributional errors when used in an autoregressive rollout setting. We propose a structured latent-variable formulation that requires only observations of solution realizations and learns the underlying randomly forced dynamics. Our approach combines a spectral Galerkin projection with a truncated Wiener chaos expansion, yielding a principled separation between deterministic evolution and stochastic forcing. This formulation reduces the infinite-dimensional SPDE to a finite system of parametrized ordinary differential equations governing latent dynamics. The latent dynamics and stochastic forcing are jointly inferred through variational learning, enabling recovery of stochastic structure without explicit observation or simulation of noise during training. Empirical evaluation on synthetic data demonstrates state-of-the-art performance under comparable modeling assumptions on bounded and unbounded one-dimensional spatial domains. We are looking forward to seeing you! Best regards, Giulia, Salvador, Leonardo, Antonio, Kristoffer and David