Robert Legenstein

83 papers A* 6A 3B 1C 1Journal 50Unranked 19

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Scalable Hybrid Training Approach for Recurrent Spiking Neural Networks. CoRR Maximilian Baronig, Yeganeh Bahariasl, Ozan Özdenizci, Robert Legenstein
2025	—	`conf`	Adversarially Robust Spiking Neural Networks with Sparse Connectivity. CPAL Mathias Schmolli, Maximilian Baronig, Robert Legenstein, Ozan Özdenizci
2025	J	`jnl`	Adversarially Robust Spiking Neural Networks with Sparse Connectivity. CoRR Mathias Schmolli, Maximilian Baronig, Robert Legenstein, Ozan Özdenizci
2025	—	`conf`	Controlling ReRAM's Switching Characteristics with Shadow Memory for Continual Learning. IMW Sai Sukruth Bezugam, Tinish Bhattacharya, Horst Petschenig, S. Choi, George Higgins Hutchinson, Giacomo Pedretti, X. Sheng, Jim Ignowski, Thomas Van Vaerenbergh, Raymond G. Beausoleil, Robert Legenstein, Dmitri B. Strukov
2025	J	`jnl`	Memory-Dependent Computation and Learning in Spiking Neural Networks Through Hebbian Plasticity. IEEE Trans. Neural Networks Learn. Syst. Thomas Limbacher, Ozan Özdenizci, Robert Legenstein
2025	A*	`conf`	Privacy-Aware Lifelong Learning. ICLR Ozan Özdenizci, Elmar Rueckert, Robert Legenstein
2025	J	`jnl`	Privacy-Aware Lifelong Learning. CoRR Ozan Özdenizci, Elmar Rueckert, Robert Legenstein
2024	J	`jnl`	Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator. CoRR Alejandro Linares-Barranco, Luciano Prono, Robert Legenstein, Giacomo Indiveri, Charlotte Frenkel
2024	J	`jnl`	Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation. CoRR Maximilian Baronig, Romain Ferrand, Silvester Sabathiel, Robert Legenstein
2024	J	`jnl`	Adversarially Robust Spiking Neural Networks Through Conversion. Trans. Mach. Learn. Res. Ozan Özdenizci, Robert Legenstein
2024	J	`jnl`	Learning-to-learn enables rapid learning with phase-change memory-based in-memory computing. CoRR Thomas Ortner, Horst Petschenig, Athanasios Vasilopoulos, Roland Renner, Spela Brglez, Thomas Limbacher, Enrique Piñero, Alejandro Linares-Barranco, Angeliki Pantazi, Robert Legenstein
2024	—	`conf`	Preserving Real-World Robustness of Neural Networks Under Sparsity Constraints. ECML/PKDD (5) Jasmin Viktoria Gritsch, Robert Legenstein, Ozan Özdenizci
2023	J	`jnl`	Adversarially Robust Spiking Neural Networks Through Conversion. CoRR Ozan Özdenizci, Robert Legenstein
2023	—	`conf`	Context-Dependent Computations in Spiking Neural Networks with Apical Modulation. ICANN (1) Romain Ferrand, Maximilian Baronig, Thomas Limbacher, Robert Legenstein
2023	J	`jnl`	Editorial: Focus on algorithms for neuromorphic computing. Neuromorph. Comput. Eng. Robert Legenstein, Arindam Basu, Priyadarshini Panda
2023	—	`conf`	Fault Pruning: Robust Training of Neural Networks with Memristive Weights. UCNC Ceca Kraisnikovic, Spyros Stathopoulos, Themis Prodromakis, Robert Legenstein
2023	—	`conf`	Interaction of Generalization and Out-of-Distribution Detection Capabilities in Deep Neural Networks. ICANN (10) Francisco Javier Klaiber Aboitiz, Robert Legenstein, Ozan Özdenizci
2023	J	`jnl`	Quantized rewiring: hardware-aware training of sparse deep neural networks. Neuromorph. Comput. Eng. Horst Petschenig, Robert Legenstein
2023	J	`jnl`	Restoring Vision in Adverse Weather Conditions With Patch-Based Denoising Diffusion Models. IEEE Trans. Pattern Anal. Mach. Intell. Ozan Özdenizci, Robert Legenstein
2022	J	`jnl`	Cortical oscillations support sampling-based computations in spiking neural networks. PLoS Comput. Biol. 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
2022	A*	`conf`	Improving Robustness Against Stealthy Weight Bit-Flip Attacks by Output Code Matching. CVPR Ozan Özdenizci, Robert Legenstein
2022	J	`jnl`	Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. CoRR Thomas Limbacher, Ozan Özdenizci, Robert Legenstein
2022	J	`jnl`	Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models. CoRR Ozan Özdenizci, Robert Legenstein
2021	—	`conf`	Dynamic Action Inference with Recurrent Spiking Neural Networks. ICANN (5) Manuel Traub, Martin V. Butz, Robert Legenstein, Sebastian Otte
2021	A	`conf`	Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks. IROS Manuel Traub, Robert Legenstein, Sebastian Otte
2021	J	`jnl`	Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks. CoRR Manuel Traub, Robert Legenstein, Sebastian Otte
2021	—	`ch.`	Spike-Based Symbolic Computations on Bit Strings and Numbers. Neuro-Symbolic Artificial Intelligence Ceca Kraisnikovic, Wolfgang Maass, Robert Legenstein
2021	A*	`conf`	Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling. ICML Ozan Özdenizci, Robert Legenstein
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`	Emergence of Stable Synaptic Clusters on Dendrites Through Synaptic Rewiring. Frontiers Comput. Neurosci. Thomas Limbacher, Robert Legenstein
2020	A*	`conf`	H-Mem: Harnessing synaptic plasticity with Hebbian Memory Networks. NeurIPS Thomas Limbacher, Robert Legenstein
2020	J	`jnl`	Oscillatory background activity implements a backbone for sampling-based computations in spiking neural networks. CoRR Michael G. Müller, Robert Legenstein
2020	J	`jnl`	The location of the axon initial segment affects the bandwidth of spike initiation dynamics. PLoS Comput. Biol. Christophe Verbist, Michael G. Müller, Huibert D. Mansvelder, Robert Legenstein, Michele Giugliano
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`	Fast learning synapses with molecular spin valves via selective magnetic potentiation. CoRR Alberto Riminucci, Robert Legenstein
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
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	A	`conf`	Bayesian modelling of student misconceptions in the one-digit multiplication with probabilistic programming. LAK Behnam Taraghi, Anna Saranti, Robert Legenstein, Martin Ebner
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`	Computer science: Nanoscale connections for brain-like circuits. Nat. Robert Legenstein
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
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	—	`ch.`	Recurrent Network Models, Reservoir Computing. Encyclopedia of Computational Neuroscience Robert Legenstein
2013	J	`jnl`	Integration of nanoscale memristor synapses in neuromorphic computing architectures CoRR Giacomo Indiveri, Bernabé Linares-Barranco, Robert Legenstein, George Deligeorgis, Themistoklis Prodromakis
2011	J	`jnl`	Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 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
2010	A*	`conf`	Combining predictions for accurate recommender systems. KDD Michael Jahrer, Andreas Töscher, Robert Legenstein
2010	J	`jnl`	Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons. Neural Comput. Lars Büsing, Benjamin Schrauwen, Robert Legenstein
2010	J	`jnl`	Reinforcement Learning on Slow Features of High-Dimensional Input Streams. PLoS Comput. Biol. Robert Legenstein, Niko Wilbert, Laurenz Wiskott
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	J	`jnl`	Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components. Neural Comput. Stefan Klampfl, Robert Legenstein, 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	—	`conf`	On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing. NIPS Benjamin Schrauwen, Lars Buesing, Robert Legenstein
2008	J	`jnl`	On the Classification Capability of Sign-Constrained Perceptrons. Neural Comput. Robert Legenstein, Wolfgang Maass
2007	J	`jnl`	Edge of chaos and prediction of computational performance for neural circuit models. Neural Networks Robert Legenstein, Wolfgang Maass
2007	—	`conf`	Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity. NIPS Robert Legenstein, Dejan Pecevski, Wolfgang Maass
2006	—	`conf`	Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons. NIPS Stefan Klampfl, Robert Legenstein, Wolfgang Maass
2005	—	`conf`	A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity. NIPS Robert Legenstein, Wolfgang Maass
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`	At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks. NIPS Nils Bertschinger, Thomas Natschläger, Robert Legenstein
2004	—	`conf`	Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits. NIPS Wolfgang Maass, Robert Legenstein, Nils Bertschinger
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
2001	J	`jnl`	Neural Circuits for Pattern Recognition with Small Total Wire Length Electron. Colloquium Comput. Complex. Robert Legenstein, Wolfgang Maass
2001	J	`jnl`	On the Complexity of Knock-knee Channel-Routing with 3-Terminal Nets Electron. Colloquium Comput. Complex. Robert Legenstein
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	—	`conf`	Foundations for a Circuit Complexity Theory of Sensory Processing. NIPS Robert Legenstein, Wolfgang Maass