List of works - Wolfgang Maaß

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

scientific article

A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware

scientific article published in 2022

A learning rule for very simple universal approximators consisting of a single layer of perceptrons

scientific article

A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback

scientific article

A quantitative analysis of information about past and present stimuli encoded by spikes of A1 neurons

scientific article

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task

scientific article

A solution to the learning dilemma for recurrent networks of spiking neurons

scientific article published on 17 July 2020

A spiking neuron as information bottleneck

scientific article

A statistical analysis of information-processing properties of lamina-specific cortical microcircuit models

scientific article published on 15 February 2006

Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity

scientific article

Belief propagation in networks of spiking neurons

scientific article published in September 2009

Branch-specific plasticity enables self-organization of nonlinear computation in single neurons.

scientific article published in July 2011

Coding and learning of behavioral sequences

scientific article published on January 2004

Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity

scientific article

Computational aspects of feedback in neural circuits

scientific article

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

scientific article (publication date: 2015)

Distributed fading memory for stimulus properties in the primary visual cortex

scientific article

Emergence of complex computational structures from chaotic neural networks through reward-modulated Hebbian learning

scientific article

Emergence of dynamic memory traces in cortical microcircuit models through STDP.

scientific article

Emergence of optimal decoding of population codes through STDP.

scientific article published on 21 March 2013

Energy-efficient neural network chips approach human recognition capabilities

scientific article published on 04 October 2016

Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environment

scientific article

Fading memory and kernel properties of generic cortical microcircuit models

scientific article

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs

scientific article

Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons

scientific article

Learned graphical models for probabilistic planning provide a new class of movement primitives

scientific article published on January 2012

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity

scientific article published on March 2016

Motif distribution, dynamical properties, and computational performance of two data-based cortical microcircuit templates

scientific article

Network Plasticity as Bayesian Inference ⬇️

scientific article published on 6 November 2015

Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons

scientific article

On the computational power of threshold circuits with sparse activity

scientific article

Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons

scientific article

Probing real sensory worlds of receivers with unsupervised clustering

scientific article

Real-time computing without stable states: a new framework for neural computation based on perturbations

scientific article (publication date: November 2002)

Reward-modulated Hebbian learning of decision making

scientific article published in June 2010

STDP installs in Winner-Take-All circuits an online approximation to hidden Markov model learning

scientific article

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons

scientific article published on 30 March 2016

Spiking neurons can learn to solve information bottleneck problems and extract independent components

scientific article published in April 2009

State-dependent computations: spatiotemporal processing in cortical networks

scientific article

Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1 ⬇️

scientific article published on November 24, 2010

Stochastic computations in cortical microcircuit models

scientific article published on 14 November 2013

List of works by Wolfgang Maaß

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware

A learning rule for very simple universal approximators consisting of a single layer of perceptrons

A learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedback

A quantitative analysis of information about past and present stimuli encoded by spikes of A1 neurons

A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task

A solution to the learning dilemma for recurrent networks of spiking neurons

A spiking neuron as information bottleneck

A statistical analysis of information-processing properties of lamina-specific cortical microcircuit models

Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity

Belief propagation in networks of spiking neurons

Branch-specific plasticity enables self-organization of nonlinear computation in single neurons.

Coding and learning of behavioral sequences

Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity

Computational aspects of feedback in neural circuits

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Distributed fading memory for stimulus properties in the primary visual cortex

Emergence of complex computational structures from chaotic neural networks through reward-modulated Hebbian learning

Emergence of dynamic memory traces in cortical microcircuit models through STDP.

Emergence of optimal decoding of population codes through STDP.

Energy-efficient neural network chips approach human recognition capabilities

Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environment

Fading memory and kernel properties of generic cortical microcircuit models

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs

Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons

Learned graphical models for probabilistic planning provide a new class of movement primitives

Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity

Motif distribution, dynamical properties, and computational performance of two data-based cortical microcircuit templates

Network Plasticity as Bayesian Inference ⬇️

Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons

On the computational power of threshold circuits with sparse activity

Probabilistic inference in general graphical models through sampling in stochastic networks of spiking neurons

Probing real sensory worlds of receivers with unsupervised clustering

Real-time computing without stable states: a new framework for neural computation based on perturbations

Reward-modulated Hebbian learning of decision making

STDP installs in Winner-Take-All circuits an online approximation to hidden Markov model learning

Solving Constraint Satisfaction Problems with Networks of Spiking Neurons

Spiking neurons can learn to solve information bottleneck problems and extract independent components

State-dependent computations: spatiotemporal processing in cortical networks

Statistical Comparison of Spike Responses to Natural Stimuli in Monkey Area V1 With Simulated Responses of a Detailed Laminar Network Model for a Patch of V1 ⬇️

Stochastic computations in cortical microcircuit models