3 citations · 7 across the 22 of their papers we have counts for
4 papers · 1 filter
Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset
Haitz Sáez de Ocáriz Borde, Flavio Savarino, Andrei Cristian Popescu +3
We introduce a dataset of approximately 10,000 Reynolds-Averaged Navier-Stokes (RANS) simulations of steady, incompressible, two-dimensional subsonic flow around downforce-generati…
Algorithmic Foundations of Deep Learning: Complexity-Theoretic Rates and a Characterization of Universal Approximation
Anastasis Kratsios, Simone Brugiapaglia, Bum Jun Kim +2
Feedforward neural network (NN) expressivity is typically studied by emulating optimal basis-expansion schemes. While powerful, this perspective is incomplete: it primarily capture…
Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity
Anastasis Kratsios, Gregory Cousins, Haitz Sáez de Ocáriz Borde +2
We show that, in a precise sense, a broad class of feedforward neural networks learn (have finite sample complexity) in the PAC model: every fixed finite feedforward architecture w…
k-Maximum Inner Product Attention for Graph Transformers and the Expressive Power of GraphGPS
Jonas De Schouwer, Haitz Sáez de Ocáriz Borde, Xiaowen Dong
Graph transformers have shown promise in overcoming limitations of traditional graph neural networks, such as oversquashing and difficulties in modeling long-range dependencies. Ho…