Geometric structure of shallow neural networks and constructive L2 cost minimization. - Thomas Chen; Patricia Muñoz Ewald (CoRR, 2023)

Geometric structure of Deep Learning networks and construction of global L2 minimizers. - Thomas Chen; Patricia Muñoz Ewald (CoRR, 2023)

Non-approximability of constructive global L2 minimizers by gradient descent in Deep Learning. - Thomas Chen; Patricia Muñoz Ewald (CoRR, 2023)

Interpretable global minima of deep ReLU neural networks on sequentially separable data. - Thomas Chen; Patricia Muñoz Ewald (CoRR, 2024)

Gradient flow in parameter space is equivalent to linear interpolation in output space. - Thomas Chen; Patricia Muñoz Ewald (CoRR, 2024)

Architecture independent generalization bounds for overparametrized deep ReLU networks. - Thomas Chen; Chun-Kai Kevin Chien; Patricia Muñoz Ewald; Andrew G. Moore (CoRR, 2025)

Explicit neural network classifiers for non-separable data. - Patricia Muñoz Ewald (CoRR, 2025)