Walter Senn

发表

Pattern Generation by Two Coupled Time-Discrete Neural Networks with Synaptic Depression

Walter Senn, Thierry Wannier, J. Kleinle, 1998, Neural Computation.

A model of expectation effects in inferior temporal cortex

Volodya Yakovlev, Ehud Zohary, Walter Senn, 2001, Neurocomputing.

Learning Only When Necessary: Better Memories of Correlated Patterns in Networks with Bounded Synapses

Walter Senn, Stefano Fusi, W. Senn, 2005, Neural Computation.

Firing Rate Adaptation without Losing Sensitivity to Input Fluctuations

Walter Senn, Hans-Rudolf Lüscher, Stefano Fusi, 2002, ICANN.

Synaptic weight decay with selective consolidation enables fast learning without catastrophic forgetting

Michael H. Herzog, Walter Senn, Pascal Leimer, 2019, bioRxiv.

Reading Neuronal Synchrony with Depressing Synapses

Idan Segev, Misha Tsodyks, Walter Senn, 1998, Neural Computation.

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

Michele Giugliano, Walter Senn, Stefano Fusi, 2008, Biological Cybernetics.

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

Walter Senn, Stefano Fusi, Giancarlo La Camera, 2004, Neurocomputing.

Special issue on object localization

Walter Senn, Christian Leibold, 2008, Biological Cybernetics.

Prospective Coding by Spiking Neurons

Johanni Brea, Walter Senn, Robert Urbanczik, 2016, PLoS Comput. Biol..

Learning temporal integration from internal feedback

Walter Senn, Erik Nygren, Emre Aksay, 2019, bioRxiv.

25th Annual Computational Neuroscience Meeting: CNS-2016

Morten L. Kringelbach, Majid Nili Ahmadabadi, Anders M. Dale, 2016, BMC Neuroscience.

Versatile Emulation of Spiking Neural Networks on an Accelerated Neuromorphic Substrate

Andreas Hartel, Walter Senn, Gerd Kiene, 2019, International Symposium on Circuits and Systems.

Fast and deep neuromorphic learning with time-to-first-spike coding pdf

Walter Senn, Laura Kriener, Mihai A. Petrovici, 2019, ArXiv.

Learning direction selectivity through spike-timing dependent modification of neurotransmitter release probability

Walter Senn, Nissim J. Buchs, 2001, Neurocomputing.

Neurons that Remember How We Got There

Johanni Brea, Walter Senn, 2015, Neuron.

Special issue on quantitative neuron modeling

Wulfram Gerstner, Felix Schürmann, Walter Senn, 2008, Biological Cybernetics.

Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible pdf

Yoshua Bengio, Walter Senn, Olexa Bilaniuk, 2016, ArXiv.

Modulating the Granularity of Category Formation by Global Cortical States

Walter Senn, Yihwa Kim, Boris B. Vladimirskiy, 2008, Frontiers Comput. Neurosci..

A deep learning framework for neuroscience

Surya Ganguli, Yoshua Bengio, Claudia Clopath, 2019, Nature Neuroscience.

Hebb in perspective

Walter Senn, J. Leo van Hemmen, 2002, Biological Cybernetics.

Sequence learning with hidden units in spiking neural networks

Jean-Pascal Pfister, Johanni Brea, Walter Senn, 2011, NIPS.

A Normative Theory of Forgetting: Lessons from the Fruit Fly

Johanni Brea, Walter Senn, Robert Urbanczik, 2014, PLoS Comput. Biol..

Gradient estimation in dendritic reinforcement learning

Walter Senn, Robert Urbanczik, Mathieu Schiess, 2012, Journal of mathematical neuroscience.

An Algorithm for Modifying Neurotransmitter Release Probability Based on Pre- and Postsynaptic Spike Timing

Henry Markram, Misha Tsodyks, Walter Senn, 2001, Neural Computation.

Eluding oblivion with smart stochastic selection of synaptic updates.

Walter Senn, Stefano Fusi, W. Senn, 2006, Chaos.

Conductance-based dendrites perform reliability-weighted opinion pooling

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2020, NICE.

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

Martin Schneider, Walter Senn, Berthold Ruf, 2002, Neural Computation.

Spatial But Not Oculomotor Information Biases Perceptual Memory: Evidence From Face Perception and Cognitive Modeling

Fred W. Mast, Walter Senn, Andrea L. Wantz, 2017, Cogn. Sci..

Beyond spike timing: the role of nonlinear plasticity and unreliable synapses

Walter Senn, W. Senn, 2002, Biological Cybernetics.

The response of cortical neurons to in vivo-like input current: theory and experiment

Michele Giugliano, Walter Senn, Stefano Fusi, 2008, Biological Cybernetics.

Spike-Timing-Dependent Plasticity, Learning Rules

Jean-Pascal Pfister, Walter Senn, W. Senn, 2014, Encyclopedia of Computational Neuroscience.

Policy gradient rules for populations of spiking neurons

Walter Senn, Robert Urbanczik, Johannes Friedrich, 2011, BMC Neuroscience.

Fast and energy-efficient neuromorphic deep learning with first-spike times

Walter Senn, Laura Kriener, Sebastian Billaudelle, 2019, Nature Machine Intelligence.

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning

Walter Senn, Roland Schäfer, Eleni Vasilaki, 2009, PLoS Comput. Biol..

Scale-Free Navigational Planning by Neuronal Traveling Waves

Walter Senn, Robert Urbanczik, Azadeh Khajeh-Alijani, 2015, PloS one.

Dendritic cortical microcircuits approximate the backpropagation algorithm

Yoshua Bengio, Walter Senn, Rui Ponte Costa, 2018, NeurIPS.

A Gradient Learning Rule for the Tempotron

Walter Senn, Robert Urbanczik, 2009, Neural Computation.

Natural gradient learning for spiking neurons

Walter Senn, Mihai A. Petrovici, Elena Kreutzer, 2020, NICE.

Decision letter: Energy efficient synaptic plasticity

Walter Senn, 2019 .

When NMDA Receptor Conductances Increase Inter-spike Interval Variability

Walter Senn, Hans-Rudolf Lüscher, Stefano Fusi, 2002, ICANN.

Reinforcement learning in populations of spiking neurons

Walter Senn, Robert Urbanczik, 2008 .

Perceptual Learning via Modification of Cortical Top-Down Signals

Walter Senn, Roland Schäfer, Eleni Vasilaki, 2007, PLoS Comput. Biol..

Comparison of two models for pattern generation based on synaptic depression

Joël Tabak, Walter Senn, Michael J. O'Donovan, 1999, Neurocomputing.

Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks pdf

Yoshua Bengio, Walter Senn, Thomas Mesnard, 2019, ArXiv.

Learning Real-World Stimuli in a Neural Network with Spike-Driven Synaptic Dynamics

Walter Senn, Stefano Fusi, Joseph M. Brader, 2007, Neural Computation.

Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Mathematical Analysis

Walter Senn, Nissim J. Buchs, W. Senn, 2003, Journal of Computational Neuroscience.

An Algorithm for Synaptic Modification Based on Exact Timing of Pre- and Post-Synaptic Action Potentials

Henry Markram, Misha Tsodyks, Walter Senn, 1997, ICANN.

Reinforcement Learning in Cortical Networks

Jean-Pascal Pfister, Walter Senn, W. Senn, 2014, Encyclopedia of Computational Neuroscience.

Walter Senn, Robert Urbanczik, W. Senn, 2001, SIAM J. Appl. Math..

Minimal Models of Adapted Neuronal Response to In VivoLike Input Currents

Walter Senn, Hans-Rudolf Lüscher, Stefano Fusi, 2004, Neural Computation.

Mathematical modeling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

Walter Senn, Christian Mazza, Simon G. Sprecher, 2018 .

Spike-based Decision Learning of Nash Equilibria in Two-Player Games

Walter Senn, Johannes Friedrich, W. Senn, 2012, PLoS Comput. Biol..

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites

Walter Senn, Robert Urbanczik, Mathieu Schiess, 2016, PLoS Comput. Biol..

Recruitment of reticulospinal neurones and steady locomotion in lamprey

Walter Senn, Thierry Wannier, W. Senn, 1998, Neural Networks.

Spatio-Temporal Credit Assignment in Neuronal Population Learning

Walter Senn, Robert Urbanczik, Johannes Friedrich, 2011, PLoS Comput. Biol..

Spike-Based Synaptic Plasticity and the Emergence of Direction Selective Simple Cells: Simulation Results

Walter Senn, Nissim J. Buchs, W. Senn, 2002, Journal of Computational Neuroscience.

Learning Spike-Based Population Codes by Reward and Population Feedback

Walter Senn, Robert Urbanczik, Johannes Friedrich, 2010, Neural Computation.

Stochasticity from function - why the Bayesian brain may need no noise

Johannes Schemmel, Karlheinz Meier, Walter Senn, 2018, Neural Networks.

Hierarchical Novelty-Familiarity Representation in the Visual System by Modular Predictive Coding

Walter Senn, Robert Urbanczik, Boris B. Vladimirskiy, 2015, PloS one.

Modulation of orientation-selective neurons by motion: when additive, when multiplicative?

Walter Senn, Robert Urbanczik, Torsten Lüdge, 2014, Front. Comput. Neurosci..

Learning flexible sensori-motor mappings in a complex network

Xiao-Jing Wang, Walter Senn, Stefano Fusi, 2009, Biological Cybernetics.

Dendritic error backpropagation in deep cortical microcircuits pdf

Yoshua Bengio, Walter Senn, Rui Ponte Costa, 2017, ArXiv.

Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses

Walter Senn, Jakob Jordan, Thomas Nevian, 2020, bioRxiv.

Spiking neurons with short-term synaptic plasticity form superior generative networks

Johannes Schemmel, Karlheinz Meier, Walter Senn, 2018, Scientific Reports.

Stimulus sampling as an exploration mechanism for fast reinforcement learning

Walter Senn, Robert Urbanczik, Eleni Vasilaki, 2009, Biological Cybernetics.

Dynamics of a random neural network with synaptic depression

Matthew E. Larkum, Walter Senn, Thierry Wannier, 1996, Neural Networks.

Slow stochastic learning with global inhibition: a biological solution to the binary perceptron problem

Walter Senn, Stefano Fusi, 2004, Neurocomputing.

Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate

Andreas Hartel, Walter Senn, Gerd Kiene, 2020, ISCAS.

Code-Specific Learning Rules Improve Action Selection by Populations of Spiking Neurons

Walter Senn, Robert Urbanczik, Johannes Friedrich, 2014, Int. J. Neural Syst..

Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail

Wulfram Gerstner, Walter Senn, Robert Urbanczik, 2009, PLoS Comput. Biol..

Evolving to learn: discovering interpretable plasticity rules for spiking networks

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2020 .

Reinforcement learning in dendritic structures

Walter Senn, Robert Urbanczik, Mathieu Schiess, 2011, BMC Neuroscience.

Statistical modelling of navigational decisions based on intensity versus directionality in Drosophila larval phototaxis

Walter Senn, Christian Mazza, Simon G Sprecher, 2018, Scientific Reports.

Size principle and information theory

Walter Senn, J. Kleinle, Hans-Rudolf Lüscher, 1997, Biological Cybernetics.

Learning cortical representations through perturbed and adversarial dreaming

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2021 .

Uncovering Neuronal Learning Principles through Artificial Evolution

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2021, ERCIM News.

Evolving neuronal plasticity rules using cartesian genetic programming

Walter Senn, Maximilian Schmidt, Jakob Jordan, 2021, GECCO Companion.

Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons pdf

Walter Senn, Laura Kriener, Jakob Jordan, 2021, NeurIPS.

Memory semantization through perturbed and adversarial dreaming pdf

Walter Senn, Jakob Jordan, Mihai A. Petrovici, 2021, ArXiv.

Repetitive TMS over the human oculomotor cortex: Comparison of 1-Hz and theta burst stimulation

Walter Senn, René M. Müri, Pascal Wurtz, 2006, Neuroscience Letters.

Hyperpolarization-activated current Ih disconnects somatic and dendritic spike initiation zones in layer V pyramidal neurons.

Walter Senn, W. Senn, H. Lüscher, 2003, Journal of neurophysiology.

A cospectral correction model for measurement of turbulent NO2 flux

Walter Senn, Werner Eugster, W. Senn, 1995 .

Nerve Injury-Induced Neuropathic Pain Causes Disinhibition of the Anterior Cingulate Cortex

Jean-Pascal Pfister, Walter Senn, Mirko Santello, 2014, The Journal of Neuroscience.

Equivalent networks of conductance- and current-driven neurons ?

Walter Senn, Stefano Fusi, Giancarlo La Camera, 2003 .