5 papers · 1 filter
Effect of Synaptic Heterogeneity on Neuronal Coordination
Moritz Layer, Moritz Helias, David Dahmen
Recent advancements in measurement techniques have resulted in an increasing amount of data on neural activities recorded in parallel, revealing largely heterogeneous correlation p…
A theory of data variability in Neural Network Bayesian inference
Javed Lindner, David Dahmen, Michael Krämer +1
Bayesian inference and kernel methods are well established in machine learning. The neural network Gaussian process in particular provides a concept to investigate neural networks…
Learning Interacting Theories from Data
Claudia Merger, Alexandre René, Kirsten Fischer +5
One challenge of physics is to explain how collective properties arise from microscopic interactions. Indeed, interactions form the building blocks of almost all physical theories…
Field theory for optimal signal propagation in ResNets
Kirsten Fischer, David Dahmen, Moritz Helias
Residual networks have significantly better trainability and thus performance than feed-forward networks at large depth. Introducing skip connections facilitates signal propagation…
Hidden connectivity structures control collective network dynamics
Lorenzo Tiberi, David Dahmen, Moritz Helias
Many observables of brain dynamics appear to be optimized for computation. Which connectivity structures underlie this fine-tuning? We propose that many of these structures are nat…