no code implementations • pproximateinference AABI Symposium 2022 • Marcello Massimo Negri, Vincent Fortuin, Jan Stuehmer
Variational auto-encoders have proven to capture complicated data distributions and useful latent representations, while advances in meta-learning have made it possible to extract prior knowledge from data.
no code implementations • 3 Jun 2022 • Fabricio Arend Torres, Marcello Massimo Negri, Monika Nagy-Huber, Maxim Samarin, Volker Roth
Physics-informed Neural Networks (PINNs) have recently emerged as a principled way to include prior physical knowledge in form of partial differential equations (PDEs) into neural networks.
no code implementations • 26 May 2023 • F. Arend Torres, Marcello Massimo Negri, Marco Inversi, Jonathan Aellen, Volker Roth
We introduce Lagrangian Flow Networks (LFlows) for modeling fluid densities and velocities continuously in space and time.
2 code implementations • NeurIPS 2023 • Marcello Massimo Negri, F. Arend Torres, Volker Roth
Studying conditional independence among many variables with few observations is a challenging task.