Robert Legenstein

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 43

Top Topics

Biologically Inspired

Bayesian Inference

Diffusion Models

Top Venues

PLoS Comput. Biol.

Neuromorph. Comput. Eng.

Publications

Ozan Özdenizci, Robert Legenstein
Adversarially Robust Spiking Neural Networks Through Conversion. Trans. Mach. Learn. Res. 2024 (2024)
Alejandro Linares-Barranco, Luciano Prono, Robert Legenstein, Giacomo Indiveri, Charlotte Frenkel
Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator. CoRR (2024)
Thomas Ortner, Horst Petschenig, Athanasios Vasilopoulos, Roland Renner, Spela Brglez, Thomas Limbacher, Enrique Piñero, Alejandro Linares Barranco, Angeliki Pantazi, Robert Legenstein
Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing. CoRR (2024)
Ozan Özdenizci, Robert Legenstein
Restoring Vision in Adverse Weather Conditions With Patch-Based Denoising Diffusion Models. IEEE Trans. Pattern Anal. Mach. Intell. 45 (8) (2023)
Ceca Kraisnikovic, Spyros Stathopoulos, Themis Prodromakis, Robert Legenstein
Fault Pruning: Robust Training of Neural Networks with Memristive Weights. UCNC (2023)
Horst Petschenig, Robert Legenstein
Quantized rewiring: hardware-aware training of sparse deep neural networks. Neuromorph. Comput. Eng. 3 (2) (2023)
Ozan Özdenizci, Robert Legenstein
Adversarially Robust Spiking Neural Networks Through Conversion. CoRR (2023)
Robert Legenstein, Arindam Basu, Priyadarshini Panda
Editorial: Focus on algorithms for neuromorphic computing. Neuromorph. Comput. Eng. 3 (3) (2023)
Ozan Özdenizci, Robert Legenstein
Improving Robustness Against Stealthy Weight Bit-Flip Attacks by Output Code Matching. CVPR (2022)
Thomas Limbacher, Ozan Özdenizci, Robert Legenstein
Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. CoRR (2022)
Ozan Özdenizci, Robert Legenstein
Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models. CoRR (2022)
Agnes Korcsak-Gorzo, Michael G. Müller, Andreas Baumbach, Luziwei Leng, Oliver Julien Breitwieser, Sacha J. van Albada, Walter Senn, Karlheinz Meier, Robert Legenstein, Mihai A. Petrovici
Cortical oscillations support sampling-based computations in spiking neural networks. PLoS Comput. Biol. 18 (3) (2022)
Ozan Özdenizci, Robert Legenstein
Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling. ICML (2021)
Manuel Traub, Robert Legenstein, Sebastian Otte
Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks. CoRR (2021)
Manuel Traub, Robert Legenstein, Sebastian Otte
Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks. IROS (2021)
Manuel Traub, Martin V. Butz, Robert Legenstein, Sebastian Otte
Dynamic Action Inference with Recurrent Spiking Neural Networks. ICANN (5) (2021)
Jacques Kaiser, Michael Hoff, Andreas Konle, Juan Camilo Vasquez Tieck, David Kappel, Daniel Reichard, Anand Subramoney, Robert Legenstein, Arne Roennau, Wolfgang Maass, Rüdiger Dillmann
Embodied Synaptic Plasticity with Online Reinforcement learning. CoRR (2020)
Christophe Verbist, Michael G. Müller, Huibert D. Mansvelder, Robert Legenstein, Michele Giugliano
The location of the axon initial segment affects the bandwidth of spike initiation dynamics. PLoS Comput. Biol. 16 (7) (2020)
Thomas Limbacher, Robert Legenstein
Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring. Frontiers Comput. Neurosci. 14 (2020)
Thomas Limbacher, Robert Legenstein
H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks. NeurIPS (2020)
Michael G. Müller, Robert Legenstein
Oscillatory background activity implements a backbone for sampling-based computations in spiking neural networks. CoRR (2020)
Guillaume Bellec, Franz Scherr, Elias Hajek, Darjan Salaj, Robert Legenstein, Wolfgang Maass
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets. CoRR (2019)
Yexin Yan, David Kappel, Felix Neumärker, Johannes Partzsch, Bernhard Vogginger, Sebastian Höppner, Steve B. Furber, Wolfgang Maass, Robert Legenstein, Christian Mayr
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype. IEEE Trans. Biomed. Circuits Syst. 13 (3) (2019)
Jacques Kaiser, Michael Hoff, Andreas Konle, Juan Camilo Vasquez Tieck, David Kappel, Daniel Reichard, Anand Subramoney, Robert Legenstein, Arne Roennau, Wolfgang Maass, Rüdiger Dillmann
Embodied Synaptic Plasticity With Online Reinforcement Learning. Frontiers Neurorobotics 13 (2019)
Alberto Riminucci, Robert Legenstein
Fast learning synapses with molecular spin valves via selective magnetic potentiation. CoRR (2019)
Yexin Yan, David Kappel, Felix Neumärker, Johannes Partzsch, Bernhard Vogginger, Sebastian Höppner, Steve B. Furber, Wolfgang Maass, Robert Legenstein, Christian Mayr
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype. CoRR (2019)
Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
Long short-term memory and Learning-to-learn in networks of spiking neurons. CoRR (2018)
Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
Long short-term memory and Learning-to-learn in networks of spiking neurons. NeurIPS (2018)
Guillaume Bellec, David Kappel, Wolfgang Maass, Robert Legenstein
Deep Rewiring: Training very sparse deep networks. ICLR (Poster) (2018)
Robert Legenstein, Wolfgang Maass, Christos H. Papadimitriou, Santosh S. Vempala
Long Term Memory and the Densest K-Subgraph Problem. ITCS (2018)
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
Pattern representation and recognition with accelerated analog neuromorphic systems. CoRR (2017)
Guillaume Bellec, David Kappel, Wolfgang Maass, Robert Legenstein
Deep Rewiring: Training very sparse deep networks. CoRR (2017)
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
Pattern representation and recognition with accelerated analog neuromorphic systems. ISCAS (2017)
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
Neuromorphic hardware in the loop: Training a deep spiking network on the BrainScaleS wafer-scale system. IJCNN (2017)
David Kappel, Robert Legenstein, Stefan Habenschuss, Michael Hsieh, Wolfgang Maass
Reward-based stochastic self-configuration of neural circuits. CoRR (2017)
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
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System. CoRR (2017)
Behnam Taraghi, Anna Saranti, Robert Legenstein, Martin Ebner
Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming. LAK (2016)
Robert Legenstein, Christos H. Papadimitriou, Santosh S. Vempala, Wolfgang Maass
Variable Binding through Assemblies in Spiking Neural Networks. CoCo@NIPS (2016)
Zhaofei Yu, David Kappel, Robert Legenstein, Sen Song, Feng Chen, Wolfgang Maass
Hamiltonian synaptic sampling in a model for reward-gated network plasticity. CoRR (2016)
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
Network Plasticity as Bayesian Inference. PLoS Comput. Biol. 11 (11) (2015)
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring. NIPS (2015)
Robert Legenstein
Computer science: Nanoscale connections for brain-like circuits. Nat. 521 (7550) (2015)
David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
Network Plasticity as Bayesian Inference. CoRR (2015)
Robert Legenstein, Wolfgang Maass
Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment. PLoS Comput. Biol. 10 (10) (2014)
Giacomo Indiveri, Bernabé Linares-Barranco, Robert Legenstein, George Deligeorgis, Themistoklis Prodromakis
Integration of nanoscale memristor synapses in neuromorphic computing architectures CoRR (2013)
Marco Baglietto, Lubica Benusková, Ivo Bukovsky, Tianping Chen, Tom Heskes, Kazushi Ikeda, Fakhri Karray, Rhee Man Kil, Robert Legenstein, Jinhu Lu, Yunqian Ma, Malik Magdon-Ismail, Michael G. Paulin, Robi Polikar, Danil V. Prokhorov, Marco A. Wiering, Vicente Zarzoso
Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 22 (1) (2011)
Michael Jahrer, Andreas Töscher, Robert Legenstein
Combining predictions for accurate recommender systems. KDD (2010)
Lars Büsing, Benjamin Schrauwen, Robert Legenstein
Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons. Neural Comput. 22 (5) (2010)
Robert Legenstein, Niko Wilbert, Laurenz Wiskott
Reinforcement Learning on Slow Features of High-Dimensional Input Streams. PLoS Comput. Biol. 6 (8) (2010)
Robert Legenstein, Steven M. Chase, Andrew B. Schwartz, Wolfgang Maass
Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning. NIPS (2009)
Stefan Klampfl, Robert Legenstein, Wolfgang Maass
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components. Neural Comput. 21 (4) (2009)
Robert Legenstein, Wolfgang Maass
On the Classification Capability of Sign-Constrained Perceptrons. Neural Comput. 20 (1) (2008)
Robert Legenstein, Dejan Pecevski, Wolfgang Maass
A Learning Theory for Reward-Modulated Spike-Timing-Dependent Plasticity with Application to Biofeedback. PLoS Comput. Biol. 4 (10) (2008)
Benjamin Schrauwen, Lars Buesing, Robert Legenstein
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing. NIPS (2008)
Robert Legenstein, Wolfgang Maass
Edge of chaos and prediction of computational performance for neural circuit models. Neural Networks 20 (3) (2007)
Robert Legenstein, Dejan Pecevski, Wolfgang Maass
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity. NIPS (2007)
Stefan Klampfl, Robert Legenstein, Wolfgang Maass
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons. NIPS (2006)
Robert Legenstein, Wolfgang Maass
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity. NIPS (2005)
Robert Legenstein, Wolfgang Maass
Wire length as a circuit complexity measure. J. Comput. Syst. Sci. 70 (1) (2005)
Robert Legenstein, Christian Naeger, Wolfgang Maass
What Can a Neuron Learn with Spike-Timing-Dependent Plasticity? Neural Comput. 17 (11) (2005)
Nils Bertschinger, Thomas Natschläger, Robert Legenstein
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks. NIPS (2004)
Wolfgang Maass, Robert Legenstein, Nils Bertschinger
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits. NIPS (2004)
Wolfgang Maass, Robert Legenstein, Henry Markram
A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models. Biologically Motivated Computer Vision (2002)
Robert Legenstein, Wolfgang Maass
Neural circuits for pattern recognition with small total wire length. Theor. Comput. Sci. 287 (1) (2002)
Robert Legenstein, Wolfgang Maass
Optimizing the Layout of a Balanced Tree Electron. Colloquium Comput. Complex. 8 (069) (2001)
Robert Legenstein, Wolfgang Maass
Neural Circuits for Pattern Recognition with Small Total Wire Length Electron. Colloquium Comput. Complex. 8 (071) (2001)
Robert Legenstein, Wolfgang Maass
Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing Electron. Colloquium Comput. Complex. 8 (070) (2001)
Robert Legenstein
On the Complexity of Knock-knee Channel-Routing with 3-Terminal Nets Electron. Colloquium Comput. Complex. (076) (2001)
Robert Legenstein, Wolfgang Maass
Foundations for a Circuit Complexity Theory of Sensory Processing. NIPS (2000)