David Dahmen

According to our database, David Dahmen authored at least 12 papers between 2012 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning.

Noa Rubin, Kirsten Fischer, Javed Lindner, David Dahmen, Inbar Seroussi, Zohar Ringel, Michael Krämer, Moritz Helias

CoRR, February, 2025

On the validity of electric brain signal predictions based on population firing rates.

Torbjørn V. Ness, Tom Tetzlaff, Gaute T. Einevoll, David Dahmen

PLoS Comput. Biol., 2025

2024

Identifying the impact of local connectivity patterns on dynamics in excitatory-inhibitory networks.

Yuxiu Shao, David Dahmen, Stefano Recanatesi, Eric Shea-Brown, Srdjan Ostojic

CoRR, 2024

Critical feature learning in deep neural networks.

Kirsten Fischer, Javed Lindner, David Dahmen, Zohar Ringel, Michael Krämer, Moritz Helias

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A theory of data variability in Neural Network Bayesian inference.

Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

CoRR, 2023

Optimal signal propagation in ResNets through residual scaling.

Kirsten Fischer, David Dahmen, Moritz Helias

CoRR, 2023

2021

Event-Based Update of Synapses in Voltage-Based Learning Rules.

Jonas Stapmanns, Jan Hahne, Moritz Helias, Matthias Bolten, Markus Diesmann, David Dahmen

Frontiers Neuroinformatics, 2021

2020

The covariance perceptron: A new paradigm for classification and processing of time series in recurrent neuronal networks.

Matthieu Gilson, David Dahmen, Rubén Moreno-Bote, Andrea Insabato, Moritz Helias

PLoS Comput. Biol., 2020

Unfolding recurrence by Green's functions for optimized reservoir computing.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Capacity of the covariance perceptron.

David Dahmen, Matthieu Gilson, Moritz Helias

CoRR, 2019

2017

Integration of Continuous-Time Dynamics in a Spiking Neural Network Simulator.

Jan Hahne, David Dahmen, Jannis Schuecker, Andreas Frommer, Matthias Bolten, Moritz Helias, Markus Diesmann

Frontiers Neuroinformatics, 2017

2012

Expert Memory in Blindfold Chess960 - An Interpretation in the light of LIDA.

Eduardo Bermúdez, David Dahmen, Henry Gonzalez

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012