Wolfgang Maass

225 papers A* 24A 2B 6C 4Journal 138Unranked 45
YearRankTypeTitle / Venue / Authors
2026 J jnl
Correction: Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations.
PLoS Comput. Biol.
Javier Galván Fraile, Franz Scherr, José J. Ramasco, Anton Arkhipov, Wolfgang Maass, Claudio R. Mirasso
2024 J jnl
Brain-Inspired Computing: A Systematic Survey and Future Trends.
Proc. IEEE
Guoqi Li, Lei Deng, Huajin Tang, Gang Pan, Yonghong Tian, Kaushik Roy, Wolfgang Maass
2024 J jnl
Corrections to "Brain-Inspired Computing: A Systematic Survey and Future Trends".
Proc. IEEE
Guoqi Li, Lei Deng, Huajin Tang, Gang Pan, Yonghong Tian, Kaushik Roy, Wolfgang Maass
2024 J jnl
Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations.
PLoS Comput. Biol.
Javier Galván Fraile, Franz Scherr, José J. Ramasco, Anton Arkhipov, Wolfgang Maass, Claudio R. Mirasso
2023 J jnl
How can neuromorphic hardware attain brain-like functional capabilities?
CoRR
Wolfgang Maass
2022 J jnl
2022 roadmap on neuromorphic computing and engineering.
Neuromorph. Comput. Eng.
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Markovic, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Steve B. Furber, Emre Neftci, Franz Scherr, Wolfgang Maass, Srikanth Ramaswamy, Jonathan Tapson, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon Thorpe, Chiara Bartolozzi, Thomas A. Cleland, Christoph Posch, Shih-Chii Liu, Gabriella Panuccio, Mufti Mahmud, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, Nini Pryds
2022 J jnl
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware.
Nat. Mach. Intell.
Arjun Rao, Philipp Plank, Andreas Wild, Wolfgang Maass
2021 J jnl
2021 Roadmap on Neuromorphic Computing and Engineering.
CoRR
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Markovic, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Emre Neftci, Srikanth Ramaswamy, Jonathan Tapson, Franz Scherr, Wolfgang Maass, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon Thorpe, Chiara Bartolozzi, Thomas A. Cleland, Christoph Posch, Shih-Chii Liu, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, Nini Pryds
2021 J jnl
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware.
CoRR
Philipp Plank, Arjun Rao, Andreas Wild, Wolfgang Maass
2021 J jnl
CCN GAC Workshop: Issues with learning in biological recurrent neural networks.
CoRR
Luke Y. Prince, Ellen Boven, Roy Henha Eyono, Arna Ghosh, Joe Pemberton, Franz Scherr, Claudia Clopath, Rui Ponte Costa, Wolfgang Maass, Blake A. Richards, Cristina Savin, Katharina Anna Wilmes
2021 J jnl
Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes.
Nat. Mach. Intell.
Christoph Stöckl, Wolfgang Maass
2021 — ch.
Reservoirs Learn to Learn.
Reservoir Computing
Anand Subramoney, Franz Scherr, Wolfgang Maass
2021 — ch.
Spike-Based Symbolic Computations on Bit Strings and Numbers.
Neuro-Symbolic Artificial Intelligence
Ceca Kraisnikovic, Wolfgang Maass, Robert Legenstein
2020 J jnl
Classifying Images with Few Spikes per Neuron.
CoRR
Christoph Stöckl, Wolfgang Maass
2020 J jnl
Embodied Synaptic Plasticity with Online Reinforcement learning.
CoRR
Jacques Kaiser, Michael Hoff, Andreas Konle, Juan Camilo Vasquez Tieck, David Kappel, Daniel Reichard, Anand Subramoney, Robert Legenstein, Arne Roennau, Wolfgang Maass, Rüdiger Dillmann
2020 J jnl
Online spatio-temporal learning in deep neural networks.
CoRR
Thomas Bohnstingl, Stanislaw Wozniak, Wolfgang Maass, Angeliki Pantazi, Evangelos Eleftheriou
2020 J jnl
Recognizing Images with at most one Spike per Neuron.
CoRR
Christoph Stöckl, Wolfgang Maass
2019 J jnl
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets.
CoRR
Guillaume Bellec, Franz Scherr, Elias Hajek, Darjan Salaj, Robert Legenstein, Wolfgang Maass
2019 — ch.
Brain Computation: A Computer Science Perspective.
Computing and Software Science
Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala, Robert Legenstein
2019 J jnl
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype.
CoRR
Yexin Yan, David Kappel, Felix Neumärker, Johannes Partzsch, Bernhard Vogginger, Sebastian Höppner, Steve B. Furber, Wolfgang Maass, Robert Legenstein, Christian Mayr
2019 J jnl
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype.
IEEE Trans. Biomed. Circuits Syst.
Yexin Yan, David Kappel, Felix Neumärker, Johannes Partzsch, Bernhard Vogginger, Sebastian Höppner, Steve B. Furber, Wolfgang Maass, Robert Legenstein, Christian Mayr
2019 J jnl
Embodied Synaptic Plasticity With Online Reinforcement Learning.
Frontiers Neurorobotics
Jacques Kaiser, Michael Hoff, Andreas Konle, Juan Camilo Vasquez Tieck, David Kappel, Daniel Reichard, Anand Subramoney, Robert Legenstein, Arne Roennau, Wolfgang Maass, Rüdiger Dillmann
2019 J jnl
Neuromorphic Hardware learns to learn.
CoRR
Thomas Bohnstingl, Franz Scherr, Christian Pehle, Karlheinz Meier, Wolfgang Maass
2019 J jnl
Reservoirs learn to learn.
CoRR
Anand Subramoney, Franz Scherr, Wolfgang Maass
2018 — conf
Deep Rewiring: Training very sparse deep networks.
ICLR (Poster)
Guillaume Bellec, David Kappel, Wolfgang Maass, Robert Legenstein
2018 A conf
Long Term Memory and the Densest K-Subgraph Problem.
ITCS
Robert Legenstein, Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala
2018 A* conf
Long short-term memory and Learning-to-learn in networks of spiking neurons.
NeurIPS
Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
2018 J jnl
Long short-term memory and Learning-to-learn in networks of spiking neurons.
CoRR
Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
2018 A* conf
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons.
NeurIPS
Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
2018 J jnl
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons.
CoRR
Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos H. Papadimitriou, Amin Saberi, Santosh S. Vempala
2017 J jnl
Deep Rewiring: Training very sparse deep networks.
CoRR
Guillaume Bellec, David Kappel, Wolfgang Maass, Robert Legenstein
2017 J jnl
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System.
CoRR
Sebastian Schmitt, Johann Klaehn, Guillaume Bellec, Andreas Grübl, Maurice Guettler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Vitali Karasenko, Mitja Kleider, Christoph Koke, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, Johannes Schemmel, Karlheinz Meier
2017 B conf
Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system.
IJCNN
Sebastian Schmitt, Johann Klähn, Guillaume Bellec, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Vasilis N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, René Schüffny, Johannes Schemmel, Karlheinz Meier
2017 C conf
Pattern representation and recognition with accelerated analog neuromorphic systems.
ISCAS
Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn, Robert D. St. Louis, Anna Schroeder, Guillaume Bellec, Johannes Bill, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Eric Müller, Paul Müller, Johannes Partzsch, Thomas Pfeil, Stefan Schiefer, Stefan Scholze, Anand Subramoney, Vasilis N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
2017 J jnl
Pattern representation and recognition with accelerated analog neuromorphic systems.
CoRR
Mihai A. Petrovici, Sebastian Schmitt, Johann Klähn, David Stöckel, Anna Schroeder, Guillaume Bellec, Johannes Bill, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Maurice Güttler, Andreas Hartel, Stephan Hartmann, Dan Husmann de Oliveira, Kai Husmann, Sebastian Jeltsch, Vitali Karasenko, Mitja Kleider, Christoph Koke, Alexander Kononov, Christian Mauch, Paul Müller, Johannes Partzsch, Thomas Pfeil, Stefan Schiefer, Stefan Scholze, Anand Subramoney, Vasilis N. Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
2017 J jnl
Reward-based stochastic self-configuration of neural circuits.
CoRR
David Kappel, Robert Legenstein, Stefan Habenschuss, Michael Hsieh, Wolfgang Maass
2016 J jnl
Energy-efficient neural network chips approach human recognition capabilities.
Proc. Natl. Acad. Sci. USA
Wolfgang Maass
2016 J jnl
Hamiltonian synaptic sampling in a model for reward-gated network plasticity.
CoRR
Zhaofei Yu, David Kappel, Robert Legenstein, Sen Song, Feng Chen, Wolfgang Maass
2016 — conf
Variable Binding through Assemblies in Spiking Neural Networks.
CoCo@NIPS
Robert Legenstein, Christos H. Papadimitriou, Santosh S. Vempala, Wolfgang Maass
2015 J jnl
Network Plasticity as Bayesian Inference.
CoRR
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
2015 J jnl
Network Plasticity as Bayesian Inference.
PLoS Comput. Biol.
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
2015 — conf
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring.
NIPS
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
2015 J jnl
To Spike or Not to Spike: That Is the Question.
Proc. IEEE
Wolfgang Maass
2014 J jnl
A theoretical basis for efficient computations with noisy spiking neurons.
CoRR
Zeno Jonke, Stefan Habenschuss, Wolfgang Maass
2014 J jnl
Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment.
PLoS Comput. Biol.
Robert Legenstein, Wolfgang Maass
2014 J jnl
Noise as a Resource for Computation and Learning in Networks of Spiking Neurons.
Proc. IEEE
Wolfgang Maass
2014 J jnl
STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning.
PLoS Comput. Biol.
David Kappel, Bernhard Nessler, Wolfgang Maass
2013 J jnl
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity.
PLoS Comput. Biol.
Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass
2013 J jnl
Emergence of Optimal Decoding of Population Codes Through STDP.
Neural Comput.
Stefan Habenschuss, Helmut Puhr, Wolfgang Maass
2013 J jnl
Stochastic Computations in Cortical Microcircuit Models.
PLoS Comput. Biol.
Stefan Habenschuss, Zeno Jonke, Wolfgang Maass
2012 J jnl
Learned graphical models for probabilistic planning provide a new class of movement primitives.
Frontiers Comput. Neurosci.
Elmar A. Rückert, Gerhard Neumann, Marc Toussaint, Wolfgang Maass
2012 — conf
Liquid Computing in a Simplified Model of Cortical Layer IV: Learning to Balance a Ball.
ICANN (1)
Dimitri Probst, Wolfgang Maass, Henry Markram, Marc-Oliver Gewaltig
2012 J jnl
The role of feedback in morphological computation with compliant bodies.
Biol. Cybern.
Helmut Hauser, Auke Jan Ijspeert, Rudolf M. Füchslin, Rolf Pfeifer, Wolfgang Maass
2011 J jnl
Biologically inspired kinematic synergies enable linear balance control of a humanoid robot.
Biol. Cybern.
Helmut Hauser, Gerhard Neumann, Auke Jan Ijspeert, Wolfgang Maass
2011 J jnl
Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons.
PLoS Comput. Biol.
Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass
2011 J jnl
Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons.
PLoS Comput. Biol.
Dejan Pecevski, Lars Buesing, Wolfgang Maass
2011 J jnl
Towards a theoretical foundation for morphological computation with compliant bodies.
Biol. Cybern.
Helmut Hauser, Auke Jan Ijspeert, Rudolf M. Füchslin, Rolf Pfeifer, Wolfgang Maass
2010 — conf
10302 Abstracts Collection - Learning paradigms in dynamic environments.
Learning paradigms in dynamic environments
Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint
2010 — conf
10302 Summary - Learning paradigms in dynamic environments.
Learning paradigms in dynamic environments
Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint
2010 J jnl
A Spiking Neuron as Information Bottleneck.
Neural Comput.
Lars Buesing, Wolfgang Maass
2010 J jnl
A Theoretical Basis for Emergent Pattern Discrimination in Neural Systems Through Slow Feature Extraction.
Neural Comput.
Stefan Klampfl, Wolfgang Maass
2010 J jnl
Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity.
Frontiers Comput. Neurosci.
Johannes Bill, Klaus Schuch, Daniel Brüderle, Johannes Schemmel, Wolfgang Maass, Karlheinz Meier
2010 — ed.
Learning paradigms in dynamic environments, 25.07. - 30.07.2010
Learning paradigms in dynamic environments
Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint
2010 J jnl
Reward-Modulated Hebbian Learning of Decision Making.
Neural Comput.
Michael Pfeiffer, Bernhard Nessler, Rodney J. Douglas, Wolfgang Maass
2009 J jnl
Belief Propagation in Networks of Spiking Neurons.
Neural Comput.
Andreas Steimer, Wolfgang Maass, Rodney J. Douglas
2009 — conf
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning.
NIPS
Robert Legenstein, Steven M. Chase, Andrew B. Schwartz, Wolfgang Maass
2009 A* conf
Learning complex motions by sequencing simpler motion templates.
ICML
Gerhard Neumann, Wolfgang Maass, Jan Peters
2009 — conf
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks.
NIPS
Stefan Klampfl, Wolfgang Maass
2009 — conf
STDP enables spiking neurons to detect hidden causes of their inputs.
NIPS
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
2009 J jnl
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components.
Neural Comput.
Stefan Klampfl, Robert Legenstein, Wolfgang Maass
2008 — conf
08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications.
Recurrent Neural Networks
Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2008 — conf
08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications.
Recurrent Neural Networks
Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2008 J jnl
A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback.
PLoS Comput. Biol.
Robert Legenstein, Dejan Pecevski, Wolfgang Maass
2008 J jnl
A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
Neural Networks
Peter Auer, Harald Burgsteiner, Wolfgang Maass
2008 — conf
Hebbian Learning of Bayes Optimal Decisions.
NIPS
Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
2008 J jnl
On the Classification Capability of Sign-Constrained Perceptrons.
Neural Comput.
Robert Legenstein, Wolfgang Maass
2008 — ed.
Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008
Recurrent Neural Networks
Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass
2007 — conf
Biologically inspired kinematic synergies provide a new paradigm for balance control of humanoid robots.
Humanoids
Helmut Hauser, Gerhard Neumann, Auke Jan Ijspeert, Wolfgang Maass
2007 J jnl
Computational Aspects of Feedback in Neural Circuits.
PLoS Comput. Biol.
Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
2007 J jnl
Edge of chaos and prediction of computational performance for neural circuit models.
Neural Networks
Robert Legenstein, Wolfgang Maass
2007 — conf
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs.
ECML
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass
2007 C conf
Liquid Computing.
CiE
Wolfgang Maass
2007 — conf
Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons.
NIPS
Lars Buesing, Wolfgang Maass
2007 J jnl
Special issue on echo state networks and liquid state machines.
Neural Networks
Herbert Jaeger, Wolfgang Maass, José Carlos Príncipe
2007 — conf
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity.
NIPS
Robert Legenstein, Dejan Pecevski, Wolfgang Maass
2006 J jnl
"Imitation of life: how biology is inspiring computing" by Nancy Forbes.
Pattern Anal. Appl.
Wolfgang Maass
2006 J jnl
A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models.
Neural Networks
Alexander Kaske, Wolfgang Maass
2006 J jnl
Computational aspects of feedback in neural circuits.
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
2006 — conf
Energy Complexity and Entropy of Threshold Circuits.
ICALP (1)
Kei Uchizawa, Rodney J. Douglas, Wolfgang Maass
2006 J jnl
Energy Complexity and Entropy of Threshold Circuits.
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Kei Uchizawa, Rodney J. Douglas
2006 — conf
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons.
NIPS
Stefan Klampfl, Robert Legenstein, Wolfgang Maass
2006 J jnl
On the Computational Power of Threshold Circuits with Sparse Activity.
Neural Comput.
Kei Uchizawa, Rodney J. Douglas, Wolfgang Maass
2006 — conf
Temporal dynamics of information content carried by neurons in the primary visual cortex.
NIPS
Danko Nikolic, Stefan Häusler, Wolf Singer, Wolfgang Maass
2005 — conf
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity.
NIPS
Robert Legenstein, Wolfgang Maass
2005 J jnl
Dynamics of information and emergent computation in generic neural microcircuit models.
Neural Networks
Thomas Natschläger, Wolfgang Maass
2005 J jnl
Movement Generation with Circuits of Spiking Neurons.
Neural Comput.
Prashant Joshi, Wolfgang Maass
2005 — conf
Principles of real-time computing with feedback applied to cortical microcircuit models.
NIPS
Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
2005 J jnl
What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?
Neural Comput.
Robert Legenstein, Christian Naeger, Wolfgang Maass
2005 J jnl
Wire length as a circuit complexity measure.
J. Comput. Syst. Sci.
Robert Legenstein, Wolfgang Maass
2004 — conf
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits.
NIPS
Wolfgang Maass, Robert Legenstein, Nils Bertschinger
2004 — conf
Movement Generation and Control with Generic Neural Microcircuits.
BioADIT
Prashant Joshi, Wolfgang Maass
2004 J jnl
On the computational power of circuits of spiking neurons.
J. Comput. Syst. Sci.
Wolfgang Maass, Henry Markram
2003 — conf
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons.
NIPS
Thomas Natschläger, Wolfgang Maass
2003 J jnl
Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts.
Complex.
Stefan Häusler, Henry Markram, Wolfgang Maass
2002 — conf
A Model for Real-Time Computation in Generic Neural Microcircuits.
NIPS
Wolfgang Maass, Thomas Natschläger, Henry Markram
2002 — conf
A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models.
Biologically Motivated Computer Vision
Wolfgang Maass, Robert Legenstein, Henry Markram
2002 J jnl
Neural circuits for pattern recognition with small total wire length.
Theor. Comput. Sci.
Robert Legenstein, Wolfgang Maass
2002 C conf
On the Computational Power of Neural Microcircuit Models: Pointers to the Literature.
ICANN
Wolfgang Maass
2002 J jnl
On the Computational Power of Recurrent Circuits of Spiking Neurons
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Henry Markram
2002 J jnl
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations.
Neural Comput.
Wolfgang Maass, Thomas Natschläger, Henry Markram
2002 C conf
Reducing Communication for Distributed Learning in Neural Networks.
ICANN
Peter Auer, Harald Burgsteiner, Wolfgang Maass
2002 J jnl
Spiking neurons and the induction of finite state machines.
Theor. Comput. Sci.
Thomas Natschläger, Wolfgang Maass
2002 J jnl
Synapses as dynamic memory buffers.
Neural Networks
Wolfgang Maass, Henry Markram
2001 J jnl
Computing the Optimally Fitted Spike Train for a Synapse.
Neural Comput.
Thomas Natschläger, Wolfgang Maass
2001 J jnl
Introduction: Spiking Neurons in Neuroscience and Technology.
Neural Networks
Stephen Grossberg, Wolfgang Maass, Henry Markram
2001 J jnl
Neural Circuits for Pattern Recognition with Small Total Wire Length
Electron. Colloquium Comput. Complex.
Robert Legenstein, Wolfgang Maass
2001 — ch.
Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers.
Current Trends in Theoretical Computer Science
Wolfgang Maass
2001 J jnl
On the relevance of time in neural computation and learning.
Theor. Comput. Sci.
Wolfgang Maass
2001 J jnl
Optimizing the Layout of a Balanced Tree
Electron. Colloquium Comput. Complex.
Robert Legenstein, Wolfgang Maass
2001 J jnl
Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing
Electron. Colloquium Comput. Complex.
Robert Legenstein, Wolfgang Maass
2000 J jnl
A Model for Fast Analog Computation Based on Unreliable Synapses.
Neural Comput.
Wolfgang Maass, Thomas Natschläger
2000 J jnl
A Simple Model for Neural Computation with Firing Rates and Firing Correlations.
Electron. Colloquium Comput. Complex.
Wolfgang Maass
2000 — conf
Autonomous Fast Learning in a Mobile Robot.
Sensor Based Intelligent Robots
Wolfgang Maass, Gerald Steinbauer, Roland Koholka
2000 — conf
Finding the Key to a Synapse.
NIPS
Thomas Natschläger, Wolfgang Maass
2000 — conf
Foundations for a Circuit Complexity Theory of Sensory Processing.
NIPS
Robert Legenstein, Wolfgang Maass
2000 J jnl
Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes
Electron. Colloquium Comput. Complex.
Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
2000 J jnl
Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers.
Bull. EATCS
Wolfgang Maass
2000 J jnl
Neural Systems as Nonlinear Filters
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Eduardo D. Sontag
2000 J jnl
Neural Systems as Nonlinear Filters.
Neural Comput.
Wolfgang Maass, Eduardo D. Sontag
2000 J jnl
On Computation with Pulses
Electron. Colloquium Comput. Complex.
Wolfgang Maass
2000 J jnl
On the Complexity of Function Learning
Electron. Colloquium Comput. Complex.
Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
2000 J jnl
On the Computational Power of Winner-Take-All
Electron. Colloquium Comput. Complex.
Wolfgang Maass
2000 J jnl
On the Computational Power of Winner-Take-All.
Neural Comput.
Wolfgang Maass
2000 — conf
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics.
NIPS
Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador
1999 J jnl
Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages.
Neural Comput.
Wolfgang Maass, Eduardo D. Sontag
1999 J jnl
Dynamic Stochastic Synapses as Computational Units.
Neural Comput.
Wolfgang Maass, Anthony M. Zador
1999 B conf
Fast analog computation in networks of spiking neurons using unreliable synapses.
ESANN
Thomas Natschläger, Wolfgang Maass
1999 — conf
Neural Computation with Winner-Take-All as the Only Nonlinear Operation.
NIPS
Wolfgang Maass
1999 J jnl
On Computations with Pulses.
Inf. Comput.
Wolfgang Maass, Berthold Ruf
1999 J jnl
On the Complexity of Learning for Spiking Neurons with Temporal Coding.
Inf. Comput.
Wolfgang Maass, Michael Schmitt
1998 — conf
A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions.
NIPS
Wolfgang Maass, Eduardo D. Sontag
1998 J jnl
Efficient Learning With Virtual Threshold Gates.
Inf. Comput.
Wolfgang Maass, Manfred K. Warmuth
1998 B conf
Models for Fast Analog Computation with Spiking Neurons.
ICONIP
Wolfgang Maass
1998 J jnl
On the Effect of Analog Noise in Discrete-Time Analog Computations.
Neural Comput.
Wolfgang Maass, Pekka Orponen
1998 B conf
On the Role of Time and Space in Neural Computation.
MFCS
Wolfgang Maass
1998 — conf
Spiking Neurons.
NC
Wolfgang Maass
1997 J jnl
Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Eduardo D. Sontag
1997 J jnl
Bounds for the Computational Power and Learning Complexity of Analog Neural Nets.
SIAM J. Comput.
Wolfgang Maass
1997 — conf
Dynamic Stochastic Synapses as Computational Units.
NIPS
Wolfgang Maass, Anthony M. Zador
1997 J jnl
Fast Sigmoidal Networks via Spiking Neurons.
Neural Comput.
Wolfgang Maass
1997 J jnl
Networks of spiking neurons: The third generation of neural network models.
Neural Networks
Wolfgang Maass
1997 J jnl
On the Complexity of Learning for Spiking Neurons with Temporal Coding
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Michael Schmitt
1997 A* conf
On the Complexity of Learning for a Spiking Neuron (Extended Abstract).
COLT
Wolfgang Maass, Michael Schmitt
1997 J jnl
On the Effect of Analog Noise in Discrete-Time Analog Computations
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Pekka Orponen
1997 B conf
On the Relevance of Time in Neural Computation and Learning.
ALT
Wolfgang Maass
1996 J jnl
Computing the Maximum Bichromatic Discrepancy with Applications to Computer Graphics and Machine Learning.
J. Comput. Syst. Sci.
David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass
1996 A* conf
Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract).
COLT
Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
1996 J jnl
Lower Bounds for the Computational Power of Networks of Spiking Neurons.
Neural Comput.
Wolfgang Maass
1996 J jnl
Networks of Spiking Neurons: The Third Generation of Neural Network Models
Electron. Colloquium Comput. Complex.
Wolfgang Maass
1996 — conf
Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons.
NIPS
Wolfgang Maass
1996 — conf
On the Effect of Analog Noise in Discrete-Time Analog Computations.
NIPS
Wolfgang Maass, Pekka Orponen
1996 J jnl
The Computational Power of Spiking Neurons Depends on the Shape of the Postsynaptic Potentials
Electron. Colloquium Comput. Complex.
Wolfgang Maass, Berthold Ruf
1995 J jnl
Agnostic PAC Learning of Functions on Analog Neural Nets.
Neural Comput.
Wolfgang Maass
1995 J jnl
Editor's Foreword.
J. Comput. Syst. Sci.
Wolfgang Maass
1995 A* conf
Efficient Learning with Virtual Threshold Gates.
ICML
Wolfgang Maass, Manfred K. Warmuth
1995 J jnl
Fast Identification of Geometric Objects with Membership Queries
Inf. Comput.
William J. Bultman, Wolfgang Maass
1995 J jnl
On the Complexity of Function Learning.
Mach. Learn.
Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
1995 — conf
On the Computational Power of Noisy Spiking Neurons.
NIPS
Wolfgang Maass
1995 A* ed.
Proceedings of the Eigth Annual Conference on Computational Learning Theory, COLT 1995, Santa Cruz, California, USA, July 5-8, 1995
COLT
Wolfgang Maass
1995 A* conf
Theory and Applications of Agnostic PAC-Learning with Small Decision Trees.
ICML
Peter Auer, Robert C. Holte, Wolfgang Maass
1994 J jnl
Agnostic PAC-Learning of Functions on Analog Neural Nets
Electron. Colloquium Comput. Complex.
Wolfgang Maass
1994 J jnl
Algorithms and Lower Bounds for On-Line Learning of Geometrical Concepts.
Mach. Learn.
Wolfgang Maass, György Turán
1994 J jnl
Bounds for the Computational Power and Learning Complexity of Analog Neural Nets
Electron. Colloquium Comput. Complex.
Wolfgang Maass
1994 J jnl
Computing the Maximum Bichromatic Discrepancy, with applications to Computer Graphics and Machine Learning
Electron. Colloquium Comput. Complex.
David P. Dobkin, Dimitrios Gunopulos, Wolfgang Maass
1994 A* conf
Efficient Agnostic PAC-Learning with Simple Hypothesis.
COLT
Wolfgang Maass
1994 J jnl
Lower Bounds for the Computational Power of Networks of Spiking Neurons
Electron. Colloquium Comput. Complex.
Wolfgang Maass
1994 J jnl
Neural Nets with Superlinear VC-Dimension
Electron. Colloquium Comput. Complex.
Wolfgang Maass
1994 J jnl
Neural Nets with Superlinear VC-Dimension.
Neural Comput.
Wolfgang Maass
1994 — conf
On the Computational Complexity of Networks of Spiking Neurons.
NIPS
Wolfgang Maass
1994 J jnl
On-Line Learning of Rectangles and Unions of Rectangles.
Mach. Learn.
Zhixiang Chen, Wolfgang Maass
1993 — conf
Agnostic PAC-Learning of Functions on Analog Neural Nets.
NIPS
Wolfgang Maass
1993 A* conf
Bounds for the computational power and learning complexity of analog neural nets.
STOC
Wolfgang Maass
1993 A* conf
On the Complexity of Function Learning.
COLT
Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
1993 — conf
On the complexity of learning on neural nets.
EuroCOLT
Wolfgang Maass
1993 J jnl
The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape.
Theor. Comput. Sci.
Martin Dietzfelbinger, Wolfgang Maass
1993 J jnl
Threshold Circuits of Bounded Depth.
J. Comput. Syst. Sci.
András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán
1993 J jnl
Two Tapes Versus One for Off-Line Turing Machines.
Comput. Complex.
Wolfgang Maass, Georg Schnitger, Endre Szemerédi, György Turán
1992 — conf
A Solution of the Credit Assignment Problem in the Case of Learning Rectangles (Abstract).
AII
Zhixiang Chen, Wolfgang Maass
1992 J jnl
Lower Bound Methods and Separation Results for On-Line Learning Models.
Mach. Learn.
Wolfgang Maass, György Turán
1992 A* conf
On-line Learning of Rectangles.
COLT
Zhixiang Chen, Wolfgang Maass
1992 J jnl
The Complexity Types of Computable Sets.
J. Comput. Syst. Sci.
Wolfgang Maass, Theodore A. Slaman
1991 A* conf
Fast Identification of Geometric Objects with Membership Queries.
COLT
William J. Bultman, Wolfgang Maass
1991 A* conf
On the Computational Power of Sigmoid versus Boolean Threshold Circuits
FOCS
Wolfgang Maass, Georg Schnitger, Eduardo D. Sontag
1991 A* conf
On-Line Learning with an Oblivious Environment and the Power of Randomization.
COLT
Wolfgang Maass
1991 J jnl
The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines.
Theor. Comput. Sci.
Martin Dietzfelbinger, Wolfgang Maass, Georg Schnitger
1990 — conf
Efficient Design of Boltzmann Machines.
NIPS
Ajay Gupta, Wolfgang Maass
1990 A* conf
On the Complexity of Learning from Counterexamples and Membership Queries
FOCS
Wolfgang Maass, György Turán
1990 A* conf
On the Complexity of Learning from Counterexamples and Membership Queries (abstract).
COLT
Wolfgang Maass, György Turán
1989 B conf
Extensional Properties of Sets of Time Bounded Complexity (Extended Abstract).
FCT
Wolfgang Maass, Theodore A. Slaman
1989 A* conf
On the Complexity of Learning From Counterexamples (Extended Abstract)
FOCS
Wolfgang Maass, György Turán
1989 — conf
The Complexity Types of Computable Sets.
SCT
Wolfgang Maass, Theodore A. Slaman
1988 J jnl
Lower Bound Arguments with "Inaccessible" Numbers.
J. Comput. Syst. Sci.
Martin Dietzfelbinger, Wolfgang Maass
1988 J jnl
Meanders and Their Applications in Lower Bounds Arguments.
J. Comput. Syst. Sci.
Noga Alon, Wolfgang Maass
1988 J jnl
Motion Planning Among Time Dependent Obstacles.
Acta Informatica
Klaus Sutner, Wolfgang Maass
1988 A* conf
On the Communication Complexity of Graph Properties
STOC
András Hajnal, Wolfgang Maass, György Turán
1988 J jnl
On the Use of Inaccessible Numbers and Order Indiscernibles in Lower Bound Arguments for Random Access Machines.
J. Symb. Log.
Wolfgang Maass
1988 A* conf
The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape.
ICALP
Martin Dietzfelbinger, Wolfgang Maass
1987 J jnl
Fast Approximation Algorithms for a Nonconvex Covering Problem.
J. Algorithms
Dorit S. Hochbaum, Wolfgang Maass
1987 J jnl
Speed-Up of Turing Machines with One Work Tape and a Two-Way Input Tape.
SIAM J. Comput.
Wolfgang Maass, Amir Schorr
1987 A* conf
Threshold circuits of bounded depth
FOCS
András Hajnal, Wolfgang Maass, Pavel Pudlák, Mario Szegedy, György Turán
1987 A* conf
Two Tapes Are Better than One for Off-Line Turing Machines
STOC
Wolfgang Maass, Georg Schnitger, Endre Szemerédi
1986 — conf
An Optimal Lower Bound for Turing Machines with One Work Tape and a Two- way Input Tape.
SCT
Wolfgang Maass, Georg Schnitger
1986 A* conf
Meanders, Ramsey Theory and Lower Bounds for Branching Programs
FOCS
Noga Alon, Wolfgang Maass
1986 J jnl
On the Complexity of Nonconvex Covering.
SIAM J. Comput.
Wolfgang Maass
1986 — conf
two Lower Bound Arguments with "Inaccessible" Numbers.
SCT
Martin Dietzfelbinger, Wolfgang Maass
1985 J jnl
Approximation Schemes for Covering and Packing Problems in Image Processing and VLSI
J. ACM
Dorit S. Hochbaum, Wolfgang Maass
1985 J jnl
Variations on Promptly Simple Sets.
J. Symb. Log.
Wolfgang Maass
1984 A conf
Approximation Schemes for Covering and Packing Problems in Robotics and VLSI.
STACS
Dorit S. Hochbaum, Wolfgang Maass
1984 J jnl
On the Orbits of Hyperhypersimple Sets.
J. Symb. Log.
Wolfgang Maass
1984 A* conf
Quadratic Lower Bounds for Deterministic and Nondeterministic One-Tape Turing Machines (Extended Abstract)
STOC
Wolfgang Maass
1983 J jnl
Oracle-Dependent Properties of the Lattice of NP Sets.
Theor. Comput. Sci.
Steven Homer, Wolfgang Maass
1983 J jnl
The intervals of the lattice of recursively enumerable sets determined by major subsets.
Ann. Pure Appl. Log.
Wolfgang Maass, Michael Stob
1982 J jnl
Recursively Enumerable Generic Sets.
J. Symb. Log.
Wolfgang Maass
1978 J jnl
The Uniform Regular Set Theorem in a-Recursion Theory.
J. Symb. Log.
Wolfgang Maass
1977 J jnl
On minimal pairs and minimal degrees in higher recursion theory.
Arch. Math. Log.
Wolfgang Maass