Philipp Petersen

32 papers A* 1Journal 31

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Certified and accurate computation of function space norms of deep neural networks. CoRR Johannes Gründler, Moritz Maibaum, Philipp Petersen
2026	J	`jnl`	LAMP: Look-Ahead Mixed-Precision Inference of Large Language Models. CoRR Stanislav Budzinskiy, Marian Gloser, Tolunay Yilmaz, Ying Hong Tham, Yuanyi Lin, Wenyi Fang, Fan Wu, Philipp Petersen
2025	J	`jnl`	High-dimensional classification problems with Barron regular boundaries under margin conditions. Neural Networks Jonathan García, Philipp Petersen
2025	J	`jnl`	Minimax learning rates for estimating binary classifiers under margin conditions. CoRR Jonathan García, Philipp Petersen
2025	J	`jnl`	Numerical Error Analysis of Large Language Models. CoRR Stanislav Budzinskiy, Wenyi Fang, Longbin Zeng, Philipp Petersen
2024	J	`jnl`	Dimension-independent learning rates for high-dimensional classification problems. CoRR Andrés Felipe Lerma Pineda, Philipp Petersen, Simon Frieder, Thomas Lukasiewicz
2024	J	`jnl`	High-dimensional classification problems with Barron regular boundaries under margin conditions. CoRR Jonathan García, Philipp Petersen
2024	J	`jnl`	Mathematical theory of deep learning. CoRR Philipp Petersen, Jakob Zech
2024	J	`jnl`	The sampling complexity of learning invertible residual neural networks. CoRR YuanYuan Li, Philipp Grohs, Philipp Petersen
2023	J	`jnl`	Large Language Models for Mathematicians. CoRR Simon Frieder, Julius Berner, Philipp Petersen, Thomas Lukasiewicz
2023	A*	`conf`	Mathematical Capabilities of ChatGPT. NeurIPS Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner
2021	J	`jnl`	Deep Microlocal Reconstruction for Limited-Angle Tomography. CoRR Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen
2021	J	`jnl`	Efficient approximation of solutions of parametric linear transport equations by ReLU DNNs. Adv. Comput. Math. Fabian Laakmann, Philipp Petersen
2021	J	`jnl`	Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks. J. Sci. Comput. Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider, Gitta Kutyniok
2021	J	`jnl`	Optimal learning of high-dimensional classification problems using deep neural networks. CoRR Philipp Petersen, Felix Voigtländer
2021	J	`jnl`	The Modern Mathematics of Deep Learning. CoRR Julius Berner, Philipp Grohs, Gitta Kutyniok, Philipp Petersen
2021	J	`jnl`	Topological Properties of the Set of Functions Generated by Neural Networks of Fixed Size. Found. Comput. Math. Philipp Petersen, Mones Raslan, Felix Voigtländer
2020	J	`jnl`	Anisotropic multiscale systems on bounded domains. Adv. Comput. Math. Philipp Grohs, Gitta Kutyniok, Jackie Ma, Philipp Petersen, Mones Raslan
2020	J	`jnl`	Efficient Approximation of Solutions of Parametric Linear Transport Equations by ReLU DNNs. CoRR Fabian Laakmann, Philipp Petersen
2020	J	`jnl`	Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks. CoRR Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider, Gitta Kutyniok
2019	J	`jnl`	A Theoretical Analysis of Deep Neural Networks and Parametric PDEs. CoRR Gitta Kutyniok, Philipp Petersen, Mones Raslan, Reinhold Schneider
2019	J	`jnl`	Approximation in L CoRR Felix Voigtländer, Philipp Petersen
2019	J	`jnl`	Approximation properties of hybrid shearlet-wavelet frames for Sobolev spaces. Adv. Comput. Math. Philipp Petersen, Mones Raslan
2019	J	`jnl`	Error bounds for approximations with deep ReLU neural networks in $W^{s, p}$ norms. CoRR Ingo Gühring, Gitta Kutyniok, Philipp Petersen
2019	J	`jnl`	Extraction of Digital Wavefront Sets Using Applied Harmonic Analysis and Deep Neural Networks. SIAM J. Imaging Sci. Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen
2019	J	`jnl`	Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks. CoRR Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen
2019	J	`jnl`	Optimal Approximation with Sparsely Connected Deep Neural Networks. SIAM J. Math. Data Sci. Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen
2018	J	`jnl`	Equivalence of approximation by convolutional neural networks and fully-connected networks. CoRR Philipp Petersen, Felix Voigtländer
2018	J	`jnl`	Optimal approximation of piecewise smooth functions using deep ReLU neural networks. Neural Networks Philipp Petersen, Felix Voigtländer
2017	J	`jnl`	Optimal Approximation with Sparsely Connected Deep Neural Networks. CoRR Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen
2017	J	`jnl`	Optimal approximation of piecewise smooth functions using deep ReLU neural networks. CoRR Philipp Petersen, Felix Voigtländer
2016	J	`jnl`	Shearlet approximation of functions with discontinuous derivatives. J. Approx. Theory Philipp Petersen