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cs.LG2026
Unsupervised Physics-Informed Operator Learning through Multi-Stage Curriculum Training
Paolo Marcandelli, Natansh Mathur, Stefano Markidis +2
Solving partial differential equations remains a central challenge in scientific machine learning. Neural operators offer a promising route by learning mappings between function sp…
cs.LG2025
Partitioned Hybrid Quantum Fourier Neural Operators for Scientific Quantum Machine Learning
Paolo Marcandelli, Yuanchun He, Stefano Mariani +2
We introduce the Partitioned Hybrid Quantum Fourier Neural Operator (PHQFNO), a generalization of the Quantum Fourier Neural Operator (QFNO) for scientific machine learning. PHQFNO…