Wolfgang Maass
Orcid: 0000-0002-1178-087XAffiliations:
- Graz University of Technology, Institute for Theoretical Computer Science, Austria
- University of Illinois at Chicago, Department of Mathematics, Statistics and Computer Science, IL, USA (former)
- University of California, Berkeley, Department of Computer Science, CA, USA (former)
According to our database1,
Wolfgang Maass
authored at least 189 papers
between 1977 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on orcid.org
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on id.loc.gov
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Bibliography
2024
Proc. IEEE, June, 2024
Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations.
PLoS Comput. Biol., 2024
2023
2022
Neuromorph. Comput. Eng., 2022
Nat. Mach. Intell., 2022
2021
Proceedings of the Neuro-Symbolic Artificial Intelligence: The State of the Art, 2021
Optimized spiking neurons can classify images with high accuracy through temporal coding with two spikes.
Nat. Mach. Intell., 2021
CoRR, 2021
2020
2019
Proceedings of the Computing and Software Science - State of the Art and Perspectives, 2019
IEEE Trans. Biomed. Circuits Syst., 2019
Frontiers Neurorobotics, 2019
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets.
CoRR, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System.
CoRR, 2017
CoRR, 2017
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017
Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
2016
Proc. Natl. Acad. Sci. USA, 2016
CoRR, 2016
Proceedings of the Workshop on Cognitive Computation: Integrating neural and symbolic approaches 2016 co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), 2016
2015
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
2014
Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment.
PLoS Comput. Biol., 2014
STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning.
PLoS Comput. Biol., 2014
Proc. IEEE, 2014
CoRR, 2014
2013
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity.
PLoS Comput. Biol., 2013
2012
Learned graphical models for probabilistic planning provide a new class of movement primitives.
Frontiers Comput. Neurosci., 2012
Biol. Cybern., 2012
Liquid Computing in a Simplified Model of Cortical Layer IV: Learning to Balance a Ball.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012
2011
Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons.
PLoS Comput. Biol., 2011
Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons.
PLoS Comput. Biol., 2011
Biologically inspired kinematic synergies enable linear balance control of a humanoid robot.
Biol. Cybern., 2011
Towards a theoretical foundation for morphological computation with compliant bodies.
Biol. Cybern., 2011
2010
A Theoretical Basis for Emergent Pattern Discrimination in Neural Systems Through Slow Feature Extraction.
Neural Comput., 2010
Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity.
Frontiers Comput. Neurosci., 2010
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010
2009
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components.
Neural Comput., 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Replacing supervised classification learning by Slow Feature Analysis in spiking neural networks.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
2008
A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback.
PLoS Comput. Biol., 2008
A learning rule for very simple universal approximators consisting of a single layer of perceptrons.
Neural Networks, 2008
Neural Comput., 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications.
Proceedings of the Recurrent Neural Networks - Models, Capacities, and Applications, 20.01., 2008
Proceedings of the Recurrent Neural Networks - Models, Capacities, and Applications, 20.01., 2008
2007
Neural Networks, 2007
Neural Networks, 2007
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Biologically inspired kinematic synergies provide a new paradigm for balance control of humanoid robots.
Proceedings of the 2007 7th IEEE-RAS International Conference on Humanoid Robots, November 29th, 2007
Proceedings of the Machine Learning: ECML 2007, 2007
2006
Pattern Anal. Appl., 2006
A model for the interaction of oscillations and pattern generation with real-time computing in generic neural microcircuit models.
Neural Networks, 2006
Neural Comput., 2006
Electron. Colloquium Comput. Complex., 2006
Electron. Colloquium Comput. Complex., 2006
Temporal dynamics of information content carried by neurons in the primary visual cortex.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
2005
Dynamics of information and emergent computation in generic neural microcircuit models.
Neural Networks, 2005
Principles of real-time computing with feedback applied to cortical microcircuit models.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
2004
J. Comput. Syst. Sci., 2004
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004
Proceedings of the Biologically Inspired Approaches to Advanced Information Technology, 2004
2003
Perspectives of the high-dimensional dynamics of neural microcircuits from the point of view of low-dimensional readouts.
Complex., 2003
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
2002
Theor. Comput. Sci., 2002
Theor. Comput. Sci., 2002
Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations.
Neural Comput., 2002
Electron. Colloquium Comput. Complex., 2002
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002
On the Computational Power of Neural Microcircuit Models: Pointers to the Literature.
Proceedings of the Artificial Neural Networks, 2002
Proceedings of the Artificial Neural Networks, 2002
A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models.
Proceedings of the Biologically Motivated Computer Vision Second International Workshop, 2002
2001
Theor. Comput. Sci., 2001
Electron. Colloquium Comput. Complex., 2001
Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers.
Proceedings of the Current Trends in Theoretical Computer Science, 2001
2000
Neural Comput., 2000
Electron. Colloquium Comput. Complex., 2000
Electron. Colloquium Comput. Complex., 2000
Electron. Colloquium Comput. Complex., 2000
Neural Computation: A Research Topic for Theoretical Computer Science? Some Thoughts and Pointers.
Bull. EATCS, 2000
Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Proceedings of the Sensor Based Intelligent Robots, 2000
1999
Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages.
Neural Comput., 1999
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999
Proceedings of the 7th European Symposium on Artificial Neural Networks, 1999
1998
A Precise Characterization of the Class of Languages Recognized by Neural Nets under Gaussian and Other Common Noise Distributions.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998
Spiking Neurons.
Proceedings of the International ICSC / IFAC Symposium on Neural Computation (NC 1998), 1998
Proceedings of the Mathematical Foundations of Computer Science 1998, 1998
Models for Fast Analog Computation with Spiking Neurons.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998
1997
SIAM J. Comput., 1997
Analog Neural Nets with Gaussian or other Common Noise Distributions cannot Recognize Arbitrary Regular Languages
Electron. Colloquium Comput. Complex., 1997
Electron. Colloquium Comput. Complex., 1997
Electron. Colloquium Comput. Complex., 1997
Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997
1996
Computing the Maximum Bichromatic Discrepancy with Applications to Computer Graphics and Machine Learning.
J. Comput. Syst. Sci., 1996
Electron. Colloquium Comput. Complex., 1996
The Computational Power of Spiking Neurons Depends on the Shape of the Postsynaptic Potentials
Electron. Colloquium Comput. Complex., 1996
Noisy Spiking Neurons with Temporal Coding have more Computational Power than Sigmoidal Neurons.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996
Learning of Depth Two Neural Networks with Constant Fan-In at the Hidden Nodes (Extended Abstract).
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996
1995
Inf. Comput., April, 1995
Proceedings of the Advances in Neural Information Processing Systems 8, 1995
Proceedings of the Machine Learning, 1995
1994
Mach. Learn., 1994
Electron. Colloquium Comput. Complex., 1994
Electron. Colloquium Comput. Complex., 1994
Electron. Colloquium Comput. Complex., 1994
Proceedings of the Advances in Neural Information Processing Systems 7, 1994
Proceedings of the Seventh Annual ACM Conference on Computational Learning Theory, 1994
1993
The Complexity of Matrix Transposition on One-Tape Off-Line Turing Machines with Output Tape.
Theor. Comput. Sci., 1993
On the complexity of learning on neural nets.
Proceedings of the First European Conference on Computational Learning Theory, 1993
1992
Mach. Learn., 1992
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992
A Solution of the Credit Assignment Problem in the Case of Learning Rectangles (Abstract).
Proceedings of the Analogical and Inductive Inference, 1992
1991
Theor. Comput. Sci., 1991
Proceedings of the 32nd Annual Symposium on Foundations of Computer Science, 1991
Proceedings of the Fourth Annual Workshop on Computational Learning Theory, 1991
1990
Proceedings of the Advances in Neural Information Processing Systems 3, 1990
Proceedings of the 31st Annual Symposium on Foundations of Computer Science, 1990
On the Complexity of Learning from Counterexamples and Membership Queries (abstract).
Proceedings of the Third Annual Workshop on Computational Learning Theory, 1990
1989
Proceedings of the 30th Annual Symposium on Foundations of Computer Science, Research Triangle Park, North Carolina, USA, 30 October, 1989
Proceedings of the Fundamentals of Computation Theory, 1989
1988
On the Use of Inaccessible Numbers and Order Indiscernibles in Lower Bound Arguments for Random Access Machines.
J. Symb. Log., 1988
J. Comput. Syst. Sci., 1988
Proceedings of the 20th Annual ACM Symposium on Theory of Computing, 1988
1987
SIAM J. Comput., 1987
Proceedings of the 19th Annual ACM Symposium on Theory of Computing, 1987
1986
Proceedings of the 27th Annual Symposium on Foundations of Computer Science, 1986
An Optimal Lower Bound for Turing Machines with One Work Tape and a Two- way Input Tape.
Proceedings of the Structure in Complexity Theory, 1986
Proceedings of the Structure in Complexity Theory, 1986
1985
J. ACM, January, 1985
1984
Quadratic Lower Bounds for Deterministic and Nondeterministic One-Tape Turing Machines (Extended Abstract)
Proceedings of the 16th Annual ACM Symposium on Theory of Computing, April 30, 1984
Proceedings of the STACS 84, 1984
1983
The intervals of the lattice of recursively enumerable sets determined by major subsets.
Ann. Pure Appl. Log., 1983
1982
1978
1977
Arch. Math. Log., 1977