3 papers
cs.LG2026
Operator-informed initialization for Fourier features physics-informed neural networks
Juan Molina, Paris Perdikaris, Mircea Petrache +2
Physics-Informed Neural Networks (PINNs) typically exhibit spectral bias, where some frequencies of the target function converge more slowly than others. In this work, we analyze t…
cs.LG2024
Understanding the dynamics of the frequency bias in neural networks
Juan Molina, Mircea Petrache, Francisco Sahli Costabal +1
Recent works have shown that traditional Neural Network (NN) architectures display a marked frequency bias in the learning process. Namely, the NN first learns the low-frequency fe…
physics.med-ph2024
CConnect: Synergistic Convolutional Regularization for Cartesian T2* Mapping
Juan Molina, Alexandre Bousse, Tabita Catalán +5
Magnetic resonance imaging (MRI) is fundamental for the assessment of many diseases, due to its excellent tissue contrast characterization. This is based on quantitative techniques…