Universal Approximation Under Constraints is Possible with Transformers

7 October 2021

Papers citing "Universal Approximation Under Constraints is Possible with Transformers"

5 / 5 papers shown

Title
Approximation Rate of the Transformer Architecture for Sequence Modeling Hao Jiang Qianxiao Li 44 9 0 03 Jan 2025
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 65 1 0 14 Oct 2024
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators? T. Kajitsuka Issei Sato 26 16 0 26 Jul 2023
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 161 1,095 0 27 Apr 2021
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 228 3,202 0 24 Nov 2016