Walter Senn

Orcid: 0000-0003-3622-0497

Affiliations:
  • University of Bern, Department of Physiology, Switzerland (PhD 1993)


According to our database1, Walter Senn authored at least 69 papers between 1996 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2024
Learning efficient backprojections across cortical hierarchies in real time.
Nat. Mac. Intell., 2024

Order from chaos: Interplay of development and learning in recurrent networks of structured neurons.
CoRR, 2024

2023
Precision estimation and second-order prediction errors in cortical circuits.
CoRR, 2023

Learning beyond sensations: how dreams organize neuronal representations.
CoRR, 2023

Learning Efficient Backprojections Across Cortical Hierarchies in Real Time.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023

2022
Cortical oscillations support sampling-based computations in spiking neural networks.
PLoS Comput. Biol., 2022

2021
Fast and energy-efficient neuromorphic deep learning with first-spike times.
Nat. Mach. Intell., 2021

Uncovering Neuronal Learning Principles through Artificial Evolution.
ERCIM News, 2021

Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons.
CoRR, 2021

Memory semantization through perturbed and adversarial dreaming.
CoRR, 2021

Latent Equilibrium: Arbitrarily fast computation with arbitrarily slow neurons.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Evolving neuronal plasticity rules using cartesian genetic programming.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020
Natural gradient learning for spiking neurons.
Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020

Conductance-based dendrites perform reliability-weighted opinion pooling.
Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020



2019
Stochasticity from function - Why the Bayesian brain may need no noise.
Neural Networks, 2019

Fast and deep neuromorphic learning with time-to-first-spike coding.
CoRR, 2019

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks.
CoRR, 2019

2018
Dendritic error backpropagation in deep cortical microcircuits.
CoRR, 2018

Dendritic cortical microcircuits approximate the backpropagation algorithm.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Spiking neurons with short-term synaptic plasticity form superior generative networks.
CoRR, 2017

Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling.
Cogn. Sci., 2017

2016
Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites.
PLoS Comput. Biol., 2016

Prospective Coding by Spiking Neurons.
PLoS Comput. Biol., 2016

Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible.
CoRR, 2016

2014
Spike-Timing-Dependent Plasticity, Learning Rules.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Reinforcement Learning in Cortical Networks.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

A Normative Theory of Forgetting: Lessons from the Fruit Fly.
PLoS Comput. Biol., 2014

Code-Specific Learning Rules Improve Action Selection by Populations of Spiking Neurons.
Int. J. Neural Syst., 2014

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?
Frontiers Comput. Neurosci., 2014

2012
Spike-based Decision Learning of Nash Equilibria in Two-Player Games.
PLoS Comput. Biol., 2012

2011
Spatio-Temporal Credit Assignment in Neuronal Population Learning.
PLoS Comput. Biol., 2011

Sequence learning with hidden units in spiking neural networks.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Learning Spike-Based Population Codes by Reward and Population Feedback.
Neural Comput., 2010

2009
Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail.
PLoS Comput. Biol., 2009

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning.
PLoS Comput. Biol., 2009

A Gradient Learning Rule for the Tempotron.
Neural Comput., 2009

Stimulus sampling as an exploration mechanism for fast reinforcement learning.
Biol. Cybern., 2009

Learning flexible sensori-motor mappings in a complex network.
Biol. Cybern., 2009

2008
Modulating the granularity of category formation by global cortical states.
Frontiers Comput. Neurosci., 2008

Special issue on object localization.
Biol. Cybern., 2008

Special issue on quantitative neuron modeling.
Biol. Cybern., 2008

The response of cortical neurons to in vivo-like input current: theory and experiment: II. Time-varying and spatially distributed inputs.
Biol. Cybern., 2008

The response of cortical neurons to in vivo-like input current: theory and experiment.
Biol. Cybern., 2008

2007
Perceptual Learning via Modification of Cortical Top-Down Signals.
PLoS Comput. Biol., 2007

Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics.
Neural Comput., 2007

2005
Learning Only When Necessary: Better Memories of Correlated Patterns in Networks with Bounded Synapses.
Neural Comput., 2005

2004
Minimal Models of Adapted Neuronal Response to In Vivo-Like Input Currents.
Neural Comput., 2004

Slow stochastic learning with global inhibition: a biological solution to the binary perceptron problem.
Neurocomputing, 2004

Comparison between networks of conductance- and current-driven neurons: stationary spike rates and subthreshold depolarization.
Neurocomputing, 2004

2003
Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Mathematical Analysis.
J. Comput. Neurosci., 2003

2002
Activity-Dependent Development of Axonal and Dendritic Delays, or, Why Synaptic Transmission Should Be Unreliable.
Neural Comput., 2002

Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Simulation Results.
J. Comput. Neurosci., 2002

Beyond spike timing: the role of nonlinear plasticity and unreliable synapses.
Biol. Cybern., 2002

Hebb in perspective.
Biol. Cybern., 2002

Firing Rate Adaptation without Losing Sensitivity to Input Fluctuations.
Proceedings of the Artificial Neural Networks, 2002

When NMDA Receptor Conductances Increase Inter-spike Interval Variability.
Proceedings of the Artificial Neural Networks, 2002

2001
Similar NonLeaky Integrate-and-Fire Neurons with Instantaneous Couplings Always Synchronize.
SIAM J. Appl. Math., 2001

An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing.
Neural Comput., 2001

A model of expectation effects in inferior temporal cortex.
Neurocomputing, 2001

Learning direction selectivity through spike-timing dependent modification of neurotransmitter release probability.
Neurocomputing, 2001

1999
Comparison of two models for pattern generation based on synaptic depression.
Neurocomputing, 1999

1998
Recruitment of reticulospinal neurones and steady locomotion in lamprey.
Neural Networks, 1998

Pattern Generation by Two Coupled Time-Discrete Neural Networks with Synaptic Depression.
Neural Comput., 1998

Reading Neuronal Synchrony with Depressing Synapses.
Neural Comput., 1998

1997
Size principle and information theory.
Biol. Cybern., 1997

An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials.
Proceedings of the Artificial Neural Networks, 1997

1996
Dynamics of a random neural network with synaptic depression.
Neural Networks, 1996


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