1 code implementation • 23 Apr 2024 • Adeyemi D. Adeoye, Philipp Christian Petersen, Alberto Bemporad
This work studies a GGN method for optimizing a two-layer neural network with explicit regularization.
no code implementations • 6 Apr 2024 • A. Martina Neuman, Philipp Christian Petersen
We study the learning problem associated with spiking neural networks.
2 code implementations • NeurIPS 2023 • Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Julius Berner
We investigate the mathematical capabilities of two iterations of ChatGPT (released 9-January-2023 and 30-January-2023) and of GPT-4 by testing them on publicly available datasets, as well as hand-crafted ones, using a novel methodology.
no code implementations • 19 Dec 2022 • Philipp Christian Petersen, Anna Sepliarskaia
We study the generalization capacity of group convolutional neural networks.
no code implementations • 3 Oct 2022 • Clemens Karner, Vladimir Kazeev, Philipp Christian Petersen
We study the training of deep neural networks by gradient descent where floating-point arithmetic is used to compute the gradients.
no code implementations • 2 Jun 2022 • Andrés Felipe Lerma Pineda, Philipp Christian Petersen
We demonstrate the admissibility of this approach to a wide range of inverse problems of practical interest.
no code implementations • 17 Jan 2019 • Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan Macdonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber
We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results.