Felix Voigtlaender 个人学术档案

引用次数

	总计	2019 年至今
引用	1433	1274
h 指数	14	14
i10 指数	18	18

340

170

255

2013201420152016201720182019202020212022202320246 11 17 24 39 45 99 147 184 292 330 208

开放获取的出版物数量

查看全部

31 篇文章

2 篇文章

可查看的文章

无法查看的文章

根据资助方的强制性开放获取政策

合著作者

Philipp PetersenUniversity of Vienna在 univie.ac.at 的电子邮件经过验证
Jordy Timo van VelthovenUniversity of Vienna在 univie.ac.at 的电子邮件经过验证
Mones RaslanApplied Scientist at Zalando在 zalando.de 的电子邮件经过验证
philipp grohsUniversity of Vienna在 univie.ac.at 的电子邮件经过验证
Hartmut FührProfessor für Mathematik, RWTH Aachen在 matha.rwth-aachen.de 的电子邮件经过验证
Gitta KutyniokBavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU Munich在 math.lmu.de 的电子邮件经过验证
Dae Gwan LeeKumoh National Institute of Technology在 kumoh.ac.kr 的电子邮件经过验证
Felix WolfProfessor of Computer Science, TU Darmstadt在 tu-darmstadt.de 的电子邮件经过验证
Rémi GribonvalInria & ENS de Lyon在 ens-lyon.fr 的电子邮件经过验证
Morten NielsenProfessor of Mathematics, Aalborg University在 math.aau.dk 的电子邮件经过验证
Friedrich PhilippDr., Technische Universität Ilmenau在 tu-ilmenau.de 的电子邮件经过验证
David BöhmeComputer Scientist, Lawrence Livermore National Laboratory在 llnl.gov 的电子邮件经过验证
José Luis RomeroAssociate Professor of Mathematics, University of Vienna在 univie.ac.at 的电子邮件经过验证
Pedro Enrique López de Teruel AlcoleaProfessor of Computer Science, Universidad de Murcia在 um.es 的电子邮件经过验证
Jose María AlmiraProfessor (Associate) of Mathematics, Universidad de Murcia在 um.es 的电子邮件经过验证
Thomas JahnKatholische Universität Eichstätt-Ingolstadt在 ku.de 的电子邮件经过验证
Tino UllrichProfessor, Faculty of Mathematics, TU Chemnitz在 mathematik.tu-chemnitz.de 的电子邮件经过验证
Paul GeuchenKatholische Universität Eichstätt-Ingolstadt在 ku.de 的电子邮件经过验证
Nicki HolighausAcoustics Research Institute, Austrian Academy of Sciences在 oeaw.ac.at 的电子邮件经过验证
Julius BernerCalifornia Institute of Technology在 caltech.edu 的电子邮件经过验证

关注

Felix Voigtlaender

Catholic University Eichstätt-Ingolstadt

在 ku.de 的电子邮件经过验证 - 首页

Mathematics of Deep Learning Machine Learning Banach frame decompositions Decomposition Spaces


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P Petersen, F Voigtlaender Neural Networks 108, 296-330, 2018	512	2018
Approximation spaces of deep neural networks R Gribonval, G Kutyniok, M Nielsen, F Voigtlaender Constructive Approximation 55 (1), 259-367, 2022	123	2022
Topological properties of the set of functions generated by neural networks of fixed size P Petersen, M Raslan, F Voigtlaender Foundations of Computational Mathematics 21, 375-444, 2021	105	2021
Equivalence of approximation by convolutional neural networks and fully-connected networks P Petersen, F Voigtlaender Proceedings of the American Mathematical Society 148 (4), 1567-1581, 2020	95	2020
Identifying the root causes of wait states in large-scale parallel applications D Böhme, M Geimer, L Arnold, F Voigtlaender, F Wolf ACM Transactions on Parallel Computing (TOPC) 3 (2), 1-24, 2016	94	2016
The universal approximation theorem for complex-valued neural networks F Voigtlaender Applied and Computational Harmonic Analysis 64, 33-61, 2023	53	2023
Embedding theorems for decomposition spaces with applications to wavelet coorbit spaces F Voigtlaender Dissertation, Aachen, Techn. Hochsch., 2015, 2016	49	2016
Wavelet coorbit spaces viewed as decomposition spaces H Führ, F Voigtlaender Journal of Functional Analysis 269 (1), 80-154, 2015	45	2015
Neural network approximation and estimation of classifiers with classification boundary in a Barron class A Caragea, P Petersen, F Voigtlaender The Annals of Applied Probability 33 (4), 3039-3079, 2023	39	2023
Proof of the theory-to-practice gap in deep learning via sampling complexity bounds for neural network approximation spaces P Grohs, F Voigtlaender Foundations of Computational Mathematics, 1-59, 2023	37	2023
Embeddings of decomposition spaces F Voigtlaender American Mathematical Society 287 (1426), 2023	33*	2023
Resolution of the wavefront set using general continuous wavelet transforms J Fell, H Führ, F Voigtlaender Journal of Fourier Analysis and Applications 22 (5), 997-1058, 2016	23	2016
Sampling numbers of smoothness classes via ℓ1-minimization T Jahn, T Ullrich, F Voigtlaender Journal of Complexity 79, 101786, 2023	22	2023
Approximation in L^p(µ) with deep ReLU neural networks F Voigtlaender, P Petersen 2019 13th International conference on Sampling Theory and Applications …, 2019	17	2019
On dual molecules and convolution-dominated operators JL Romero, JT van Velthoven, F Voigtlaender Journal of Functional Analysis 280 (10), 108963, 2021	14	2021
Negative results for approximation using single layer and multilayer feedforward neural networks JM Almira, PE Lopez-de-Teruel, DJ Romero-López, F Voigtlaender Journal of mathematical analysis and applications 494 (1), 124584, 2021	13*	2021
Optimal learning of high-dimensional classification problems using deep neural networks P Petersen, F Voigtlaender arXiv preprint arXiv:2112.12555, 2021	11	2021
Design and properties of wave packet smoothness spaces D Bytchenkoff, F Voigtlaender Journal de Mathématiques Pures et Appliquées 133, 185-262, 2020	11	2020
Phase transitions in rate distortion theory and deep learning P Grohs, A Klotz, F Voigtlaender Foundations of Computational Mathematics, 1-64, 2021	9	2021
Guided performance analysis combining profile and trace tools J Giménez, J Labarta, FX Pegenaute, HF Wen, D Klepacki, IH Chung, ... European Conference on Parallel Processing, 513-521, 2010	9	2010

系统目前无法执行此操作，请稍后再试。

文章 1–20

每年引用数

重复的引用

合并的引用

添加合著者合著作者

上传 PDF

关注此作者

引用次数

合著作者

引用