Robert A. Legenstein

According to our database1, Robert A. Legenstein authored at least 37 papers between 2000 and 2019.

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Bibliography

2019
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype.
IEEE Trans. Biomed. Circuits and Systems, 2019

2018
Long short-term memory and Learning-to-learn in networks of spiking neurons.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Long Term Memory and the Densest K-Subgraph Problem.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

Deep Rewiring: Training very sparse deep networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017


2016
Variable Binding through Assemblies in Spiking Neural Networks.
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

Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming.
Proceedings of the Sixth International Conference on Learning Analytics & Knowledge, 2016

2015
Network Plasticity as Bayesian Inference.
PLoS Computational Biology, 2015

Computer science: Nanoscale connections for brain-like circuits.
Nature, 2015

Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014
Recurrent Network Models, Reservoir Computing.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment.
PLoS Computational Biology, 2014

2011
Editorial: One Year as EiC, and Editorial-Board Changes at TNN.
IEEE Trans. Neural Networks, 2011

2010
Reinforcement Learning on Slow Features of High-Dimensional Input Streams.
PLoS Computational Biology, 2010

Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons.
Neural Computation, 2010

Combining predictions for accurate recommender systems.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components.
Neural Computation, 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

2008
A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback.
PLoS Computational Biology, 2008

On the Classification Capability of Sign-Constrained Perceptrons.
Neural Computation, 2008

On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Edge of chaos and prediction of computational performance for neural circuit models.
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

2006
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005
What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?
Neural Computation, 2005

Wire length as a circuit complexity measure.
J. Comput. Syst. Sci., 2005

A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

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

At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2002
Neural circuits for pattern recognition with small total wire length.
Theor. Comput. Sci., 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
On the Complexity of Knock-knee Channel-Routing with 3-Terminal Nets
Electronic Colloquium on Computational Complexity (ECCC), 2001

Neural Circuits for Pattern Recognition with Small Total Wire Length
Electronic Colloquium on Computational Complexity (ECCC), 2001

Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing
Electronic Colloquium on Computational Complexity (ECCC), 2001

Optimizing the Layout of a Balanced Tree
Electronic Colloquium on Computational Complexity (ECCC), 2001

2000
Foundations for a Circuit Complexity Theory of Sensory Processing.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000


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