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2020 – today
- 2024
[c3]Kirsten Fischer, Javed Lindner, David Dahmen, Zohar Ringel, Michael Krämer, Moritz Helias:
Critical feature learning in deep neural networks. ICML 2024- 2023
- [i3]Kirsten Fischer, David Dahmen, Moritz Helias:
Optimal signal propagation in ResNets through residual scaling. CoRR abs/2305.07715 (2023) - [i2]Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias:
A theory of data variability in Neural Network Bayesian inference. CoRR abs/2307.16695 (2023) - 2021
- [j3]Jonas Stapmanns
, Jan Hahne, Moritz Helias, Matthias Bolten, Markus Diesmann, David Dahmen:
Event-Based Update of Synapses in Voltage-Based Learning Rules. Frontiers Neuroinformatics 15: 609147 (2021) - 2020
- [j2]Matthieu Gilson, David Dahmen, Rubén Moreno-Bote, Andrea Insabato, Moritz Helias:
The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks. PLoS Comput. Biol. 16(10) (2020) - [c2]Sandra Nestler, Christian Keup, David Dahmen, Matthieu Gilson, Holger Rauhut, Moritz Helias:
Unfolding recurrence by Green's functions for optimized reservoir computing. NeurIPS 2020
2010 – 2019
- 2019
- [i1]David Dahmen, Matthieu Gilson, Moritz Helias:
Capacity of the covariance perceptron. CoRR abs/1912.00824 (2019) - 2017
- [j1]Jan Hahne, David Dahmen, Jannis Schuecker, Andreas Frommer, Matthias Bolten, Moritz Helias, Markus Diesmann:
Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator. Frontiers Neuroinformatics 11: 34 (2017) - 2012
- [c1]Eduardo Bermúdez, David Dahmen, Henry Gonzalez:
Expert Memory in Blindfold Chess960 - An Interpretation in the light of LIDA. CogSci 2012
Coauthor Index
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