Walter Senn

According to our database1, Walter Senn authored at least 51 papers between 1996 and 2018.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Dendritic cortical microcircuits approximate the backpropagation algorithm.
CoRR, 2018

Stochasticity from function - why the Bayesian brain may need no noise.
CoRR, 2018

Dendritic error backpropagation in deep cortical microcircuits.
CoRR, 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.
Cognitive Science, 2017

2016
Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites.
PLoS Computational Biology, 2016

Prospective Coding by Spiking Neurons.
PLoS Computational Biology, 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 Computational Biology, 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?
Front. Comput. Neurosci., 2014

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

2011
Spatio-Temporal Credit Assignment in Neuronal Population Learning.
PLoS Computational Biology, 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 Computation, 2010

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

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning.
PLoS Computational Biology, 2009

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

Stimulus sampling as an exploration mechanism for fast reinforcement learning.
Biological Cybernetics, 2009

Learning flexible sensori-motor mappings in a complex network.
Biological Cybernetics, 2009

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

Special issue on object localization.
Biological Cybernetics, 2008

Special issue on quantitative neuron modeling.
Biological Cybernetics, 2008

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

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

2007
Perceptual Learning via Modification of Cortical Top-Down Signals.
PLoS Computational Biology, 2007

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

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

2004
Minimal Models of Adapted Neuronal Response to In Vivo-Like Input Currents.
Neural Computation, 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.
Journal of Computational Neuroscience, 2003

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

Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Simulation Results.
Journal of Computational Neuroscience, 2002

Beyond spike timing: the role of nonlinear plasticity and unreliable synapses.
Biological Cybernetics, 2002

Hebb in perspective.
Biological Cybernetics, 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 Journal of Applied Mathematics, 2001

An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing.
Neural Computation, 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 Computation, 1998

Reading Neuronal Synchrony with Depressing Synapses.
Neural Computation, 1998

1997
Size principle and information theory.
Biological Cybernetics, 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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