#ML4Phys

Meta-Learning Fourier Neural Operators for Hessian Inversion and Enhanced Variational Data Assimilation Data assimilation (DA) is crucial for enhancing solutions to partial differential equations (PDEs), such as those in numerical weather prediction, by optimizing initial conditions using observational ...

🚨 New paper accepted at #NeurIPS2025 #ML4Phys!

We propose Meta-Learning Fourier Neural Operators to approximate inverse Hessians for variational data assimilation.

Great week at @neuripsconf.bsky.social ! Excited to present my work on GFlowNets for Chemistry in Quantum Computers at the Machine Learning and the Physical Sciences workshop with @rovargash.bsky.social 😬
#NeurIPS2024 #ml4ps2024 #ml4phys #compchem