4 papers
Training-Free Bayesian Filtering with Generative Emulators
Thomas Savary, François Rozet, Gilles Louppe
Bayesian filtering is a well-known problem that aims to estimate plausible states of a dynamical system from observations. Among existing approaches to solve this problem, particle…
Enforcing governing equation constraints in neural PDE solvers via training-free projections
Omer Rochman, Gilles Louppe
Neural PDE solvers used for scientific simulation often violate governing equation constraints. While linear constraints can be projected cheaply, many constraints are nonlinear, c…
Lost in Latent Space: An Empirical Study of Latent Diffusion Models for Physics Emulation
François Rozet, Ruben Ohana, Michael McCabe +3
The steep computational cost of diffusion models at inference hinders their use as fast physics emulators. In the context of image and video generation, this computational drawback…
Training-Free Data Assimilation with GenCast
Thomas Savary, François Rozet, Gilles Louppe
Data assimilation is widely used in many disciplines such as meteorology, oceanography, and robotics to estimate the state of a dynamical system from noisy observations. In this wo…