22 citations · 25 across the 13 of their papers we have counts for
3 papers · 1 filter
Spectral methods for Neural Integral Equations
Emanuele Zappala
Neural integral equations are deep learning models based on the theory of integral equations, where the model consists of an integral operator and the corresponding equation (of th…
Operator Learning Meets Numerical Analysis: Improving Neural Networks through Iterative Methods
Emanuele Zappala, Daniel Levine, Sizhuang He +3
Deep neural networks, despite their success in numerous applications, often function without established theoretical foundations. In this paper, we bridge this gap by drawing paral…
Continuous Spatiotemporal Transformers
Antonio H. de O. Fonseca, Emanuele Zappala, Josue Ortega Caro +1
Modeling spatiotemporal dynamical systems is a fundamental challenge in machine learning. Transformer models have been very successful in NLP and computer vision where they provide…