17 citations · 17 across the 7 of their papers we have counts for
5 papers · 1 filter
Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts
Fanny Lehmann, Firat Ozdemir, Yun Cheng +4
While AI weather models excel at short-to-medium range forecasts (up to 15 days), they frequently suffer from ill-defined "instabilities" when rolled out over longer horizons. This…
Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations
Niccolò Perrone, Fanny Lehmann, Stefania Fresca +1
Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequency content is systematically…
Finetuning a Weather Foundation Model with Lightweight Decoders for Unseen Physical Processes
Fanny Lehmann, Firat Ozdemir, Benedikt Soja +3
Recent advances in AI weather forecasting have led to the emergence of so-called "foundation models", typically defined by expensive pretraining and minimal fine-tuning for downstr…
Integrating Fourier Neural Operators with Diffusion Models to improve Spectral Representation of Synthetic Earthquake Ground Motion Response
Niccolò Perrone, Fanny Lehmann, Hugo Gabrielidis +2
Nuclear reactor buildings must be designed to withstand the dynamic load induced by strong ground motion earthquakes. For this reason, their structural behavior must be assessed in…
Multiple-Input Fourier Neural Operator (MIFNO) for source-dependent 3D elastodynamics
Fanny Lehmann, Filippo Gatti, Didier Clouteau
Numerical simulations are essential tools to evaluate the solution of the wave equation in complex settings, such as three-dimensional (3D) domains with heterogeneous properties. H…