3 papers
cs.LG2025
Spectral Analysis of Molecular Features: When Richer Features Do Not Guarantee Better Generalization
Asma Jamali, Tin Sum Cheng, Rodrigo A. Vargas-Hernández
The spectral properties of feature embeddings offer critical insights into model generalization and representation quality. While deep learning models are widely used for molecular…
cs.LG2025
Meta-Learning Fourier Neural Operators for Hessian Inversion and Enhanced Variational Data Assimilation
Hamidreza Moazzami, Asma Jamali, Nicholas Kevlahan +1
Data assimilation (DA) is crucial for enhancing solutions to partial differential equations (PDEs), such as those in numerical weather prediction, by optimizing initial conditions…
physics.chem-ph2024
MOLPIPx: an end-to-end differentiable package for permutationally invariant polynomials in Python and Rust
Manuel S. Drehwald, Asma Jamali, Rodrigo A. Vargas-Hernández
In this work, we present MOLPIPx, a versatile library designed to seamlessly integrate Permutationally Invariant Polynomials (PIPs) with modern machine learning frameworks, enablin…