Ingo Gühring

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Gitta KutyniokBavarian AI Chair for Mathematical Foundations of Artificial Intelligence, LMU MunichVerified email at math.lmu.de
Philipp PetersenUniversity of ViennaVerified email at univie.ac.at
Mones RaslanApplied Scientist at ZalandoVerified email at zalando.de
Martin GenzelStaff Machine Learning Reseacher, Merantix MomentumVerified email at merantix-momentum.com
Maximilian MärzTechnische Universität BerlinVerified email at math.tu-berlin.de
Jan MacdonaldTechnische Universität BerlinVerified email at math.tu-berlin.de
Cosmas HeißTU BerlinVerified email at math.tu-berlin.de
Martin EigelWeierstrass Institute for Applied Analysis and Stochastics BerlinVerified email at wias-berlin.de
Jun (Luke) HuanAWS AI LabsVerified email at amazon.com
Behrooz (Bernard) Omidvar-TehraniAmazonVerified email at amazon.com
Hao ZhouNorthwestern University, Amazon Web ServiceVerified email at u.northwestern.edu
Linbo LiuApplied Scientist, AWS AI LabsVerified email at amazon.com
Wooseok HaUniversity of California, BerkeleyVerified email at berkeley.edu
Ziwei FanApplied Scientist, AWS AI LabsVerified email at amazon.com
Gaurav GuptaSenior Scientist, AWS-AIVerified email at usc.edu
Hao DingSenior Applied Scientist and Manager, AWS AIVerified email at amazon.com
Shiqi WangResearch Scientist, Meta, Llama TeamVerified email at cs.columbia.edu

Ingo Gühring

Applied Scientist, AWS

Verified email at math.tu-berlin.de - Homepage

Deep Learning


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Error bounds for approximations with deep ReLU neural networks in norms I Gühring, G Kutyniok, P Petersen Analysis and Applications 18 (05), 803-859, 2020	228	2020
Approximation rates for neural networks with encodable weights in smoothness spaces I Gühring, M Raslan Neural Networks 134, 107-130, 2020	114	2020
Expressivity of deep neural networks I Gühring, M Raslan, G Kutyniok arXiv preprint arXiv:2007.04759, 2020	78	2020
Near-Exact Recovery for Tomographic Inverse Problems via Deep Learning M Genzel, I Gühring, J Macdonald, M März International Conference on Machine Learning (ICML), 2022	33	2022
Multilevel CNNs for Parametric PDEs C Heiß, I Gühring, M Eigel Journal of Machine Learning Research 24 (373), 1--42, 2023	8	2023
A neural multilevel method for high-dimensional parametric PDEs C Heiß, I Gühring, M Eigel NeurIPS workshop on The Symbiosis of Deep Learning and Differential …, 2021	7	2021
Reasoning and Planning with Large Language Models in Code Development H Ding, Z Fan, I Guehring, G Gupta, W Ha, J Huan, L Liu, ... Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024	2	2024
Approximation with Neural Networks from a Theoretical and Practical Perspective I Gühring TU Berlin, Institut für Softwaretechnik und Theoretische Informatik, 2022		2022
Near-Exact Recovery for Sparse-View CT via Data-Driven Methods M Genzel, I Gühring, J Macdonald, M Maximilian NeurIPS workshop on Deep Learning and Inverse Problems, 2021		2021
Eigenvalues in gaps of G-selfadjoint operators in Almost Pontryagin spaces I Gühring Technische Universität Berlin, 2017		2017

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