5 citations · 5 across the 2 of their papers we have counts for
4 papers
A Variational Latent Equilibrium for Learning in Neuronal Circuits
Simon Brandt, Paul Haider, Walter Senn +2
Brains remain unrivaled in their ability to recognize and generate complex spatiotemporal patterns. While AI is able to reproduce some of these capabilities, deep learning algorith…
Backpropagation through space, time, and the brain
Benjamin Ellenberger, Paul Haider, Jakob Jordan +5
How physical networks of neurons, bound by spatio-temporal locality constraints, can perform efficient credit assignment, remains, to a large extent, an open question. In machine l…
ELiSe: Efficient Learning of Sequences in Structured Recurrent Networks
Laura Kriener, Kristin Völk, Ben von Hünerbein +3
Behavior can be described as a temporal sequence of actions driven by neural activity. To learn complex sequential patterns in neural networks, memories of past activities need to…
Prospective and retrospective coding in cortical neurons
Simon Brandt, Mihai Alexandru Petrovici, Walter Senn +2
Brains can process sensory information from different modalities at astonishing speed; this is surprising as the integration of inputs through the membrane of each individual neuro…