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Moritz Helias

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A theory of data variability in Neural Network Bayesian inference

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Jul 31, 2023
Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

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Speed Limits for Deep Learning

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Jul 27, 2023
Inbar Seroussi, Alexander A. Alemi, Moritz Helias, Zohar Ringel

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Optimal signal propagation in ResNets through residual scaling

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May 12, 2023
Kirsten Fischer, David Dahmen, Moritz Helias

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Neuronal architecture extracts statistical temporal patterns

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Jan 24, 2023
Sandra Nestler, Moritz Helias, Matthieu Gilson

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Origami in N dimensions: How feed-forward networks manufacture linear separability

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Mar 21, 2022
Christian Keup, Moritz Helias

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Decomposing neural networks as mappings of correlation functions

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Feb 10, 2022
Kirsten Fischer, Alexandre René, Christian Keup, Moritz Layer, David Dahmen, Moritz Helias

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Unified Field Theory for Deep and Recurrent Neural Networks

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Jan 07, 2022
Kai Segadlo, Bastian Epping, Alexander van Meegen, David Dahmen, Michael Krämer, Moritz Helias

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Unfolding recurrence by Green's functions for optimized reservoir computing

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Oct 14, 2020
Sandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson, Holger Rauhut, Moritz Helias

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