| Título |
Autores |
Link |
Tema |
| Optimal sampling for least‑squares approximation |
Ben Adcock |
arXiv:2409.02342 |
CD kernel |
| CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions |
Ben Adcock, Juan M. Cardenas, Nick Dexter |
arXiv:2306.00945 |
CD kernel |
| Geometry and Optimization of Shallow Polynomial Networks |
Y. Arjevani, J. Bruna, J. Kileel, E. Polak, M. Trager |
arXiv:2501.06074 |
DL / Optimization |
| Geometry of Polynomial Neural Networks |
Kaie Kubjas, Jiayi Li, Maximilian Wiesmann |
arXiv:2402.00949 |
DL / Algebraic Geometry |
| Stability Properties of Graph Neural Networks |
Fernando Gama,Joan Bruna,Alejandro Ribeiro |
arXiv:1905.04497 |
DL/GNN |
| Convolutional Neural Networks on Manifolds: From Graphs and Back |
Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro |
arXiv:2210.00376 |
Geometric DL / GNNs |
The Barron Space and the Flow‑Induced Function Spaces for Neural Network Models |
Weinan E, Chao Ma, Lei Wu |
arXiv:1906.08039 |
DL |
| Operator Learning of Lipschitz Operators: An Information-Theoretic Perspective |
Samuel Lanthaler |
arXiv:2406.18794 |
DL |
| Breaking the Curse of Dimensionality with Convex Neural Networks |
Francis Bach |
arXiv:1412.8690 |
DL |