Universal Approximation Under Constraints is Possible with Transformers

7 October 2021

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

35 / 35 papers shown

Title
Approximation Rate of the Transformer Architecture for Sequence Modeling Hao Jiang Qianxiao Li 91 11 0 03 Jan 2025
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 352 1,148 0 27 Apr 2021
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization Haochuan Li Yi Tian Jingzhao Zhang Ali Jadbabaie 57 41 0 18 Apr 2021
Model-Based Domain Generalization Alexander Robey George J. Pappas Hamed Hassani OOD 73 130 0 23 Feb 2021
Elementary superexpressive activations Dmitry Yarotsky 59 35 0 22 Feb 2021
On the Regularity of Attention James Vuckovic A. Baratin Rémi Tachet des Combes 34 7 0 10 Feb 2021
Neural Network Approximation: Three Hidden Layers Are Enough Zuowei Shen Haizhao Yang Shijun Zhang 66 117 0 25 Oct 2020
Discrete-time signatures and randomness in reservoir computing Christa Cuchiero Lukas Gonon Lyudmila Grigoryeva Juan-Pablo Ortega Josef Teichmann 55 45 0 17 Sep 2020
Minimum Width for Universal Approximation Sejun Park Chulhee Yun Jaeho Lee Jinwoo Shin 68 124 0 16 Jun 2020
Globally Injective ReLU Networks Michael Puthawala K. Kothari Matti Lassas Ivan Dokmanić Maarten V. de Hoop 53 28 0 15 Jun 2020
Probably Approximately Correct Constrained Learning Luiz F. O. Chamon Alejandro Ribeiro 51 41 0 09 Jun 2020
$O(n)$ Connections are Expressive Enough: Universal Approximability of Sparse Transformers Chulhee Yun Yin-Wen Chang Srinadh Bhojanapalli A. S. Rawat Sashank J. Reddi Sanjiv Kumar 54 81 0 08 Jun 2020
Non-Euclidean Universal Approximation Anastasis Kratsios Ievgen Bilokopytov AAML 42 51 0 03 Jun 2020
Differentiating through the Fréchet Mean Aaron Lou Isay Katsman Qingxuan Jiang Serge J. Belongie Ser-Nam Lim Christopher De Sa DRL 107 64 0 29 Feb 2020
Approximation Bounds for Random Neural Networks and Reservoir Systems Lukas Gonon Lyudmila Grigoryeva Juan-Pablo Ortega 78 67 0 14 Feb 2020
Are Transformers universal approximators of sequence-to-sequence functions? Chulhee Yun Srinadh Bhojanapalli A. S. Rawat Sashank J. Reddi Sanjiv Kumar 110 354 0 20 Dec 2019
Risk bounds for reservoir computing Lukas Gonon Lyudmila Grigoryeva Juan-Pablo Ortega 65 40 0 30 Oct 2019
The phase diagram of approximation rates for deep neural networks Dmitry Yarotsky Anton Zhevnerchuk 59 121 0 22 Jun 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 128 330 0 21 May 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 81 199 0 21 Feb 2019
Differentiable reservoir computing Lyudmila Grigoryeva Juan-Pablo Ortega 42 40 0 16 Feb 2019
Generalized Sliced Wasserstein Distances Soheil Kolouri Kimia Nadjahi Umut Simsekli Roland Badeau Gustavo K. Rohde 50 300 0 01 Feb 2019
Equivalence of approximation by convolutional neural networks and fully-connected networks P. Petersen Felix Voigtländer 56 80 0 04 Sep 2018
Universality of Deep Convolutional Neural Networks Ding-Xuan Zhou HAI PINN 412 514 0 28 May 2018
geomstats: a Python Package for Riemannian Geometry in Machine Learning Nina Miolane Johan Mathe Claire Donnat Mikael Jorda Xavier Pennec AI4CE 74 128 0 21 May 2018
Optimal Transport: Fast Probabilistic Approximation with Exact Solvers Max Sommerfeld Jörn Schrieber Y. Zemel Axel Munk OT 37 54 0 14 Feb 2018
Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems Lyudmila Grigoryeva Juan-Pablo Ortega 43 66 0 03 Dec 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 698 131,526 0 12 Jun 2017
A Random Matrix Approach to Neural Networks Cosme Louart Zhenyu Liao Romain Couillet 65 161 0 17 Feb 2017
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning Stefan Elfwing E. Uchibe Kenji Doya 133 1,723 0 10 Feb 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 808 3,281 0 24 Nov 2016
First-order Methods for Geodesically Convex Optimization Hongyi Zhang S. Sra 63 292 0 19 Feb 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 323 18,613 0 06 Feb 2015
Neural Machine Translation by Jointly Learning to Align and Translate Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio AIMat 552 27,300 0 01 Sep 2014
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 215 4,262 0 04 Jun 2013