1.
B. Adcock, S. Brugiapaglia, N. Dexter and S. Moraga, Deep neural networks are effective at learning high-dimensional Hilbert-valued functions from limited data, In Proceedings of the 2nd Mathematical and Scientific Machine Learning Conference, Proceedings of Machine Learning Research, 145 (2022), 1-36.
2.
B. Adcock, S. Brugiapaglia, N. Dexter and S. Moraga, Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks, preprint, arXiv: 2211.12633, 2022.
3. B. Adcock, S. Brugiapaglia, N. Dexter and S. Moraga, Learning smooth functions in high dimensions: From sparse polynomials to deep neural networks, In Handbook of Numerical Analysis, 25 (2024), 1-52.
4. B. Adcock, S. Brugiapaglia and C. G. Webster, Sparse Polynomial Approximation of High-Dimensional Functions, Society for Industrial and Applied Mathematics, Philadelphia, PA, 2022
5. The Gap between Theory and Practice in Function Approximation with Deep Neural Networks