Superiority of GNN over NN in generalizing bandlimited functions. - A. Martina Neuman; Rongrong Wang; Yuying Xie (CoRR, 2022)

Transferability of Graph Neural Networks using Graphon and Sampling Theories. - A. Martina Neuman; Jason J. Bramburger (CoRR, 2023)

Digital Computers Break the Curse of Dimensionality: Adaptive Bounds via Finite Geometry. - Anastasis Kratsios; A. Martina Neuman; Gudmund Pammer (CoRR, 2024)

Efficient Learning Using Spiking Neural Networks Equipped With Affine Encoders and Decoders. - A. Martina Neuman; Philipp Christian Petersen (CoRR, 2024)

Convolutional dynamical sampling and some new results. - Longxiu Huang; A. Martina Neuman; Sui Tang; Yuying Xie (CoRR, 2024)

Consistency of augmentation graph and network approximability in contrastive learning. - Chenghui Li; A. Martina Neuman (CoRR, 2025)

Reconstruction of frequency-localized functions from pointwise samples via least squares and deep learning. - A. Martina Neuman; Andres Felipe Lerma Pineda; Jason J. Bramburger; Simone Brugiapaglia (CoRR, 2025)