Closing the loop: High-speed robotics with accelerated neuromorphic hardware
Yannik Stradmann, Johannes Schemmel
Frontiers in Neuroscience, Sec. Neuromorphic Engineering, Volume 18 - 2024
Spiking Neural Network Nonlinear Demapping on Neuromorphic Hardware for IM/DD Optical Communication
Arnold, Elias and Böcherer, Georg and Strasser, Florian and Müller, Eric and Spilger, Philipp and Billaudelle, Sebastian and Weis, Johannes and Schemmel, Johannes and Calabrò, Stefano and Kuschnerov, Maxim
https://ieeexplore.ieee.org/document/10059327
Autocorrelations from emergent bistability in homeostatic spiking neural networks on neuromorphic hardware
Benjamin Cramer, Markus Kreft, Sebastian Billaudelle, Vitali Karasenko, Aron Leibfried, Eric Müller, Philipp Spilger, Johannes Weis, Johannes Schemmel, Miguel A. Muñoz, Viola Priesemann, Johannes Zierenberg
From clean room to machine room: commissioning of the first-generation BrainScaleS wafer-scale neuromorphic system
Hartmut Schmidt and José Montes and Andreas Grübl and Maurice Güttler and Dan Husmann and Joscha Ilmberger and Jakob Kaiser and Christian Mauch and Eric Müller and Lars Sterzenbach and Johannes Schemmel and Sebastian Schmitt
Neuromorphic Computing and Engineering 3 (2023) 034013
Simulation-based inference for model parameterization on analog neuromorphic hardware
Jakob Kaiser, Raphael Stock, Eric Müller, Johannes Schemmel, Sebastian Schmitt
Jakob Kaiser et al 2023 Neuromorph. Comput. Eng. 3 044006
Gradient-based methods for spiking physical systems
Julian Göltz, Sebastian Billaudelle, Laura Kriener, Luca Blessing, Christian Pehle, Eric Müller, Johannes Schemmel, Mihai A. Petrovici
A flexible column parallel successive-approximation ADC for hybrid neuromorphic computing
Philipp Dauer, Milena Czierlinski, Sebastian Billaudelle, Andreas Grübl and Johannes Schemmel
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2
Philipp Spilger, Elias Arnold, Luca Blessing, Christian Mauch, Christian Pehle, Eric Müller, Johannes Schemmel
Biomorphic control for high-speed robotic applications
Yannik Stradmann, Johannes Schemmel
Quantum many-body states: A novel neuromorphic application
Andreas Baumbach , Robert Klassert , Stefanie Czischek , Martin Gärttner , Mihai A. Petrovici
NICE 2022: Neuro-Inspired Computational Elements Conference
Spiking Neural Network Equalization for IM/DD Optical Communication
Arnold E, Böcherer G, Müller E, Spilger P, Schemmel J, Calabrò S, Kuschnerov M
SPPCom (2022)
Surrogate gradients for analog neuromorphic computing
Benjamin Cramer and Sebastian Billaudelle and Simeon Kanya and Aron Leibfried and Grübl, Andreas and Vitali Karasenko and Christian Pehle and Korbinian Schreiber and Yannik Stradmann and Johannes Weis and Johannes Schemmel and Friedemann Zenke
Proceedings of the National Academy of Sciences 119 (2022)
Neuromorphic quantum computing
Christian Pehle and Christof Wetterich
Neuromorphic quantum computing
Christian Pehle and Christof Wetterich
Physical Review E, Vol. 106, No. 4
Spiking Neural Network Equalization on Neuromorphic Hardware for IM/DD Optical Communication
Elias Arnold and Georg Böcherer and Eric Müller and Philipp Spilger and Johannes Schemmel and Stefano Calabrò and Maxim Kuschnerov
Spiking Neural Network Equalization for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
Spiking Neural Network Equalization on Neuromorphic Hardware for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Eric Müller, Philipp Spilger, Johannes Schemmel, Stefano Calabrò, Maxim Kuschnerov
The Operating System of the Neuromorphic BrainScaleS-1 System
Eric Müller, Sebastian Schmitt, Christian Mauch, Sebastian Billaudelle, Andreas Grübl, Maurice Güttler, Dan Husmann, Joscha Ilmberger, Sebastian Jeltsch, Jakob Kaiser, Johann Klähn, Mitja Kleider, Christoph Koke, José Montes, Paul Müller, Johannes Partzsch, Felix Passenberg, Hartmut Schmidt, Bernhard Vogginger, Jonas Weidner, Christian Mayr, Johannes Schemmel
Neurocomputing (2022)
Emulating Dendritic Computing Paradigms on Analog Neuromorphic Hardware
Jakob Kaiser, Sebastian Billaudelle, Eric Müller, Christian Tetzlaff, Johannes Schemmel, Sebastian Schmitt
Neuroscience 489 (2022) 290-300
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware
Müller E, Arnold E, Breitwieser O, Czierlinski M, Emmel A, Kaiser J, Mauch C, Schmitt S, Spilger P, Stock R, Stradmann Y, Weis J, Baumbach A, Billaudelle S, Cramer B, Ebert F, Göltz J, Ilmberger J, Karasenko V, Kleider M, Leibfried A, Pehle C and Schemmel J
Front. Neurosci. 16 (2022) 884128
The BrainScaleS-2 Accelerated Neuromorphic System With Hybrid Plasticity
Pehle C, Billaudelle S, Cramer B, Kaiser J, Schreiber K, Stradmann Y, Weis J, Leibfried A, Müller E and Schemmel J
Front. Neurosci. 16 (2022) 795876
Demonstrating BrainScaleS-2 Inter-Chip Pulse Communication using EXTOLL
Thommes T, Bordukat S, Grübl A, Karasenko V, Müller E, Schemmel, J
NICE (2022) 98--100
Towards Addressing Noise and Static Variations of Analog Computations using Efficient Retraining
Bernhard Klein, Lisa Kuhn, Johannes Weis, Arne Emmel, Yannik Stradmann, Johannes Schemmel, Holger Fröning
Predictive olfactory learning in Drosophila
Chang Zhao, Yves F. Widmer, Soeren Diegelmann, Mihai A. Petrovici, Simon G. Sprecher, Walter Senn
Scientific Reports volume 11, Article number: 6795 (2021)
Visualizing a joint future of neuroscience and neuromorphic engineering
Friedemann Zenke and Sander M. Bohté and Claudia Clopath and Iulia M. Comşa and Julian Göltz and Wolfgang Maass and Timothée Masquelier and Richard Naud and Emre O. Neftci and Mihai A. Petrovici and Franz Scherr and Dan F.M. Goodman
Neuron 109 (2021) 571-575
Fast and energy-efficient neuromorphic deep learning with first-spike times
J. Göltz, L. Kriener, A. Baumbach, S. Billaudelle, O. Breitwieser, B. Cramer, D. Dold, A. F. Kungl, W. Senn, J. Schemmel, K. Meier, M. A. Petrovici
Nature Machine Intelligence volume 3 (2021) 823–835
Learning Bayes-optimal dendritic opinion pooling
Jakob Jordan, João Sacramento, Willem A.M. Wybo, Mihai A. Petrovici*, Walter Senn*
arXiv:2104.13238
The Yin-Yang dataset
Laura Kriener and Julian Göltz and Mihai A. Petrovici
arXiv:2102.08211
Event-based backpropagation can compute exact gradients for spiking neural networks
Wunderlich, Timo C. and Pehle, Christian
Demonstrating Analog Inference on the BrainScaleS-2 Mobile System
Yannik Stradmann, Sebastian Billaudelle, Oliver Breitwieser, Falk Leonard Ebert, Arne Emmel, Dan Husmann, Joscha Ilmberger, Eric Müller, Philipp Spilger, Johannes Weis, Johannes Schemmel
arXiv:2103.15960
Self-sustained probabilistic computing on spike-based neuromorphic systems
Akos F. Kungl, Dominik Dold, Andreas Baumbach, Oliver Breitwieser, Ilja Bytschok, Andreas Grübl, Nico Gürtler, Maurice Güttler, Andreas Hartel, Dan Husmann, Kai Husmann, Vitali Karasenko, Johann Klähn, Mitja Kleider, Christoph Koke, Alexander Kugele, Luziwei Leng, Christian Mauch, Eric Müller, Paul Müller, Sebastian Schmitt, Karlheinz Meier, Johannes Schemmel, Walter Senn and Mihai A. Petrovici
Bernstein Conference - Online only, 2020
Deep reinforcement learning for time-continuous substrates
Akos F. Kungl, Dominik Dold, Oskar Riedler, Mihai A. Petrovici, Walter Senn
Neuro-Inspired Computational Elements Workshop (NICE), 2020 Heidelberg, Germany
Verification and Design Methods for the BrainScaleS Neuromorphic Hardware System
Andreas Grübl, Sebastian Billaudelle, Benjamin Cramer, Vitali Karasenko, Johannes Schemmel
Control of criticality and computation in spiking neuromorphic networks with plasticity
Benjamin Cramer, David Stöckel, Markus Kreft, Michael Wibral, Johannes Schemmel, Karlheinz Meier, Viola Priesemann
Nature Communications 11 (2020) 1-11
The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
Benjamin Cramer, Yannik Stradmann, Johannes Schemmel, Friedemann Zenke
IEEE Transactions on Neural Networks and Learning Systems (2020)
Natural gradient learning for spiking neurons
E. Kreutzer, M. A. Petrovici, W. Senn
COSYNE 2020, NICE 2020
Natural gradient learning for spiking neurons
Elena Kreutzer, Walter Senn*, Mihai A. Petrovici*
arXiv:2011.11710
Extending BrainScaleS OS for BrainScaleS-2
Eric Müller, Christian Mauch, Philipp Spilger, Oliver Julien Breitwieser, Johann Klähn, David Stöckel, Timo C. Wunderlich, Johannes Schemmel
https://arxiv.org/abs/2003.13750
Fast and deep neuromorphic learning with first-spike coding
J. Göltz, A. Baumbach, S. Billaudelle, O. Breitwieser, L. Kriener, A. F. Kungl, K. Meier, J. Schemmel, M. A. Petrovici
NICE 2020, NAISYS 2020, COSYNE 2020
Evolving to learn: discovering interpretable plasticity rules for spiking networks
Jakob Jordan*, Maximilian Schmidt*, Walter Senn, Mihai A. Petrovici
arXiv:2005.14149
Conductance-based dendrites perform reliability-weighted opinion pooling
Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento
NAISYS 2020, NICE 2020
Accelerated Analog Neuromorphic Computing
Johannes Schemmel, Sebastian Billaudelle, Philipp Dauer, Johannes Weis
https://arxiv.org/abs/2003.11996
Inference with Artificial Neural Networks on Analog Neuromorphic Hardware
Johannes Weis, Philipp Spilger, Sebastian Billaudelle, Yannik Stradmann, Arne Emmel, Eric Müller, Oliver Breitwieser, Andreas Grübl, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Christian Mauch, Korbinian Schreiber, Johannes Schemmel
Communications in Computer and Information Science, vol 1325 (2020), pp 201-212
Closed-loop experiments on the BrainScaleS-2 architecture
K. Schreiber, T. C. Wunderlich, C. Pehle, M. A. Petrovici, J. Schemmel, K. Meier
Neuro-Inspired Computational Elements Workshop (NICE), 2020 Heidelberg, Germany
hxtorch: PyTorch for BrainScaleS-2 -- Perceptrons on Analog Neuromorphic Hardware
Philipp Spilger, Eric Müller, Arne Emmel, Aron Leibfried, Christian Mauch, Christian Pehle, Johannes Weis, Oliver Breitwieser, Sebastian Billaudelle, Sebastian Schmitt, Timo C. Wunderlich, Yannik Stradmann, Johannes Schemmel
https://arxiv.org/abs/2006.13138
Structural plasticity on spiking neuromorphic hardware
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici, Johannes Schemmel
Neuro-Inspired Computational Elements Workshop (NICE) 2020
Spiking neuromorphic chip learns entangled quantum states
Stefanie Czischek, Andreas Baumbach, Sebastian Billaudelle, Benjamin Cramer, Lukas Kades, Jan M. Pawlowski, Markus K. Oberthaler, Johannes Schemmel, Mihai A. Petrovici, Thomas Gasenzer, Martin Gärttner
SciPost Phys. 12, 039 (2022)
Deep reinforcement learning in a time-continuous model
Akos F. Kungl, Dominik Dold, Oskar Riedler, Mihai A. Petrovici, Walter Senn
Bernstein Conference - Berlin, 2019
Accelerated physical emulation of Bayesian inference in spiking neural networks
Akos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Frontiers in Neuroscience 13 (2019) 1201
Magnetic phenomena in ensembles of spiking neurons
Andreas Baumbach, Johannes Schemmel, Mihai Petrovici
Bernstein Conference - Berlin, 2019
Stochasticity from function - why the Bayesian brain may need no noise
Dominik Dold*, Ilja Bytschok*, Akos F. Kungl, Andreas Baumbach, Oliver Breitwieser, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici*
Neural Networks 119 (2019)
Lagrangian dynamics of dendritic microcircuits enables real-time backpropagation of errors
Dominik Dold, Akos F. Kungl, João Sacramento, Mihai A. Petrovici, Kaspar Schindler, Jonathan Binas, Yoshua Bengio, Walter Senn
Cosyne abstracts 2019, Lisbon, Portugal
An energy-based model of folded autoencoders for unsupervised learning in cortical hierarchies
Dominik Dold, João Sacramento, Akos F. Kungl, Walter Senn and Mihai A. Petrovici
Bernstein Conference - Berlin, 2019
Error-driven learning supports Bayes-optimal multisensory integration via conductance-based dendrites
Jakob Jordan, João Sacramento, Mihai A Petrovici, Walter Senn
Cosyne abstracts 2019, Lisbon, Portugal
Deterministic networks for probabilistic computing
Jakob Jordan, Mihai A. Petrovici, Oliver Breitwieser, Johannes Schemmel, Karlheinz Meier, Markus Diesmann, Tom Tetzlaff
Scientific Reports 9, 18303 (2019)
Fast and deep neuromorphic learning with time-to-first-spike coding
Julian Göltz, Andreas Baumbach, Sebastian Billaudelle, Oliver Breitwieser, Dominik Dold, Laura Kriener, Akos Ferenc Kungl, Walter Senn, Johannes Schemmel, Karlheinz Meier, Mihai Alexandru Petrovici
arXiv preprint arXiv:1912.11443
Biological solutions to the mixing problem (2019 IRCN best poster award)
Luziwei Leng, Agnes Korcsák-Gorzó, Oliver Breitwieser, Roman Martel, Ilja Bytschok, Walter Senn, Johannes Bill, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
2019 IRCN poster
Structural plasticity on an accelerated analog neuromorphic hardware system
Sebastian Billaudelle* and Benjamin Cramer* and Mihai A. Petrovici and Korbinian Schreiber and David Kappel and Johannes Schemmel^ and Karlheinz Meier^
Neural Networks (2021) 11-20
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
Sebastian Billaudelle*, Yannik Stradmann*, Korbinian Schreiber*, Benjamin Cramer*, Andreas Baumbach*, Dominik Dold*, Julian Göltz*, Akos F. Kungl*, Timo C. Wunderlich*, Andreas Hartel, Eric Müller, Oliver Breitwieser, Christian Mauch, Mitja Kleider, Andreas Grübl, David Stöckel, Christian Pehle, Arthur Heimbrecht, Philipp Spilger, Gerd Kiene, Vitali Karasenko, Walter Senn, Mihai A. Petrovici^, Johannes Schemmel^, Karlheinz Meier^
2020 IEEE International Symposium on Circuits and Systems (ISCAS) (pp. 1-5). IEEE
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
Timo C. Wunderlich, Akos F. Kungl, Eric Müller, Johannes Schemmel, Mihai Petrovici
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation (2019)
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
Timo Wunderlich, Akos F. Kungl, Eric Müller, Andreas Hartel, Yannik Stradmann, Syed Ahmed Aamir, Andreas Grübl, Arthur Heimbrecht, Korbinian Schreiber, David Stöckel, Christian Pehle, Sebastian Billaudelle, Gerd Kiene, Christian Mauch, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Frontiers in Neuroscience
Magnetic Phenomena in Spiking Neural Networks
A. Baumbach, A. F. Kungl, M. A. Petrovici, J. Schemmel, K. Meier
Fruehjahrstagung der DPG
Generative models on accelerated neuromorphic hardware
Akos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
CNS - Computational Neuroscience Conference - 2018 Seattle
Training and deployment of hierarchical inference networks on a physical neuromorphic substrate
Akos F. Kungl, Sebastian Schmitt, Johann Klähn, Paul Müller, Andreas Baumbach, Dominik Dold, Alexander Kugele, Nico Gürtler, Luziwei Leng, Eric Müller, Christoph Koke, Mitja Kleider, Christian Mauch, Oliver Breitwieser, Maurice Güttler, Dan Husmann, Kai Husmann, Joscha Ilmberger, Andreas Hartel, Vitali Karasenko, Andreas Grübl, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Bernstein Conference - 2018 Berlin
Spiking neurons with short-term synaptic plasticity form superior generative networks
Luziwei Leng*, Roman Martel, Oliver Breitwieser, Ilja Bytschok, Walter Senn, Johannes Schemmel, Karlheinz Meier & Mihai A. Petrovici*
Scientific Reports 8, 10651 (2018)
An Accelerated LIF Neuronal Network Array for a Large Scale Mixed-Signal Neuromorphic Architecture
Syed Ahmed Aamir*, Yannik Stradmann*, Paul Müller, Christian Pehle, Andreas Hartel, Andreas Grübl, Johannes Schemmel and Karlheinz Meier
IEEE Transactions on Circuits and Systems I: Regular Papers
A Mixed-Signal Structured AdEx Neuron for Accelerated Neuromorphic Cores
Syed Ahmed Aamir, Paul Müller, Gerd Kiene, Laura Kriener, Yannik Stradmann, Andreas Grübl, Johannes Schemmel and Karlheinz Meier
IEEE Transactions on Biomedical Circuits and Systems
Large-Scale Neuromorphic Spiking Array Processors: A Quest to Mimic the Brain
Thakur, Chetan Singh and Molin, Jamal Lottier and Cauwenberghs, Gert and Indiveri, Giacomo and Kumar, Kundan and Qiao, Ning and Schemmel, Johannes and Wang, Runchun and Chicca, Elisabetta and Olson Hasler, Jennifer and Seo, Jae-sun and Yu, Shimeng and Cao, Yu and van Schaik, André and Etienne-Cummings, Ralph
Frontiers in Neuroscience 12 (2018) 891
Bayesian computing with spikes
A. Baumbach, M. A. Petrovici, L. Leng, O. J. Breitwieser, D. Stoeckel, I. Bytschok, J. Schemmel, K. Meier
1st HBP Student Conference
Simulated Tempering in Biologically Inspired Neural Networks
Agnes Korcsak-Gorzo, Luziwei Leng, Oliver Julien Breitwieser, Johannes Schemmel, Karlheinz Meier, Mihai Alexandru Petrovici
Deutsche Physikerinnentagung
Stochastic computation on spiking neuromorphic hardware
Dominik Dold, Ákos F. Kungl, Andreas Baumbach, Johann Klähn, Ilja Bytschok, Paul Müller, Oliver Breitwieser, Andreas Grübl, Maurice Güttler, Dan Husmann, Mitja Kleider, Christoph Koke, Alexander Kugele, Christian Mauch, Eric Müller, Sebastian Schmitt, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
Bernstein Conference 2017
Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System
Friedmann, Schemmel, Grübl, Hartel, Hock, Meier
IEEE Transactions on Biomedical Circuits and Systems
Spike-based probabilistic inference with correlated noise
Ilja Bytschok, Dominik Dold, Johannes Schemmel, Karlheinz Meier, Mihai A. Petrovici
BMC Neuroscience 2017, 18 (Suppl 1):P200
An Accelerated Analog Neuromorphic Hardware System Emulating NMDA- and Calcium-Based Non-Linear Dendrites
Johannes Schemmel, Laura Kriener, Paul Müller, Karlheinz Meier
Proceedings of the 2017 IEEE International Joint Conference on Neural Networks
Full Wafer Redistribution and Wafer Embedding as Key Technologies for a Multi-Scale Neuromorphic Hardware Cluster
Kai Zoschke, Maurice Güttler, Lars Böttcher, Andreas Grübl, Dan Husmann, Johannes Schemmel, Karlheinz Meier, Oswin Ehrmann
arXiv:1801.04734
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware
Mihai A. Petrovici*, Anna Schroeder*, Oliver Breitwieser, Andreas Grübl, Johannes Schemmel, Karlheinz Meier
Proceedings of the 2017 IEEE International Joint Conference on Neural Networks
Pattern representation and recognition with accelerated analog neuromorphic systems
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, 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 Thanasoulis, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, René Schüffny, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Proceedings of the 2017 IEEE International Symposium on Circuits and Systems (ISCAS)
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Sebastian Schmitt*, Johann Klaehn*, Guillaume Bellec, Andreas Gruebl, Maurice Guettler, Andreas Hartel, Stephan Hartmann, Dan Husmann, Kai Husmann, Vitali Karasenko, Mitja Kleider, Christoph Koke, Christian Mauch, Eric Mueller, Paul Mueller, Johannes Partzsch, Mihai A. Petrovici, Stefan Schiefer, Stefan Scholze, Bernhard Vogginger, Robert Legenstein, Wolfgang Maass, Christian Mayr, Johannes Schemmel, Karlheinz Meier
Proceedings of the 2017 IEEE International Joint Conference on Neural Networks
From LIF to AdEx Neuron Models: Accelerated Analog 65 nm CMOS Implementation
Syed Ahmed Aamir* , Paul Müller*, Laura Kriener, Gerd Kiene, Johannes Schemmel and Karlheinz Meier
Accepted at 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses
Alexander Serb, Johannes Bill, Ali Khiat, Radu Berdan, Robert Legenstein and Themis Prodromakis
Nature Communications 7 (2016) 12611
Spiking neural networks as superior generative and discriminative models
Luziwei Leng*, Mihai A. Petrovici*, Roman Martel, Ilja Bytschok, Oliver Breitwieser, Johannes Bill, Johannes Schemmel, Karlheinz Meier
Cosyne Abstracts 2016, Salt Lake City USA
Form Versus Function: Theory and Models for Neuronal Substrates
Mihai A. Petrovici
Springer Theses
Stochastic inference with spiking neurons in the high-conductance state
Mihai A. Petrovici*, Johannes Bill*, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
Physical Review E 94, 042312 (2016)
Stochastic inference with spiking neural networks
Mihai A. Petrovici*, Luziwei Leng*, Oliver Breitwieser*, David Stöckel*, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier
BMC Neuroscience 2016, 17(Suppl 1):P96
A highly tunable 65-nm CMOS LIF neuron for a large scale neuromorphic system
Syed Ahmed Aamir, Paul Müller, Andreas Hartel, Johannes Schemmel and Karlheinz Meier
Proceedings of IEEE European Solid-State Circuits Conference
Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware Study
Thomas Pfeil and Jakob Jordan and Tom Tetzlaff and Andreas Grübl and Johannes Schemmel and Markus Diesmann and Karlheinz Meier
Phys. Rev. X 6 (2016) 021023
Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons
Dimitri Probst*, Mihai A. Petrovici*, Ilja Bytschok, Johannes Bill, Dejan Pecevski, Johannes Schemmel, Karlheinz Meier
Frontiers in Computational Neurocience (February 2015)
Deterministic neural networks as sources of uncorrelated noise for probabilistic computations
Jakob Jordan, Tom Tetzlaff, Mihai Petrovici, Oliver Breitwieser, Ilja Bytschok, Johannes Bill, Johannes Schemmel, Karlheinz Meier and Markus Diesmann
BMC Neuroscience 2015, 16(Suppl 1):P62
Fast sampling with neuromorphic hardware
Mihai A. Petrovici*, David Stöckel*, Ilja Bytschok, Johannes Bill, Thomas Pfeil, Johannes Schemmel, Karlheinz Meier
Advances in Neural Information Processing Systems (NIPS) 2015
The high-conductance state enables neural sampling in networks of LIF neurons
Mihai A. Petrovici, Ilja Bytschok, Johannes Bill, Johannes Schemmel and Karlheinz Meier
BMC Neuroscience 2015, 16(Suppl 1):O2
Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms
Mihai A. Petrovici, Bernhard Vogginger, Paul Müller, Oliver Breitwieser, Mikael Lundqvist, Lyle Muller, Matthias Ehrlich, Alain Destexhe, Anders Lansner, René Schüffny, Johannes Schemmel, Karlheinz Meier
PLOS ONE (2014)
A neuromorphic network for generic multivariate data classification
Michael Schmuker, Thomas Pfeil and Martin Paul Nawrot
Proceedings of the National Academy of Sciences (2014)
Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate
Simon Friedmann, Nicolas Frémaux, Johannes Schemmel, Wulfram Gerstner, and Karlheinz Meier
Frontiers in Neuroscience Vol. 7 (2013) 160
An analog dynamic memory array for neuromorphic hardware
Matthias Hock, Andreas Hartel, Johannes Schemmel, Karlheinz Meier
Circuit Theory and Design (ECCTD), 2013 European Conference on
Stochastic inference with deterministic spiking neurons
Mihai A. Petrovici*, Johannes Bill*, Ilja Bytschok, Johannes Schemmel, Karlheinz Meier
arXiv:1311.3211
Six networks on a universal neuromorphic computing substrate
Thomas Pfeil, Andreas Grübl, Sebastian Jeltsch, Eric Müller, Paul Müller, Mihai A. Petrovici, Michael Schmuker, Daniel Brüderle, Johannes Schemmel, Karlheinz Meier
Front. Neurosci. vol. 7, no. 11, 2013
Neuromorphic Learning towards Nano Second Precision
Thomas Pfeil, Anne-Christine Scherzer, Johannes Schemmel and Karlheinz Meier
Proceedings of International Joint Conference on Neural Networks, Dallas, Texas, USA, August 4-9, 2013, IEEE Press (2013), pp. 1-5
Live demonstration: A scaled-down version of the BrainScaleS wafer-scale neuromorphic system
Schemmel, J. and Grubl, A. and Hartmann, S. and Kononov, A. and Mayr, C. and Meier, K. and Millner, S. and Partzsch, J. and Schiefer, S. and Scholze, S. and Schuffny, R. and Schwartz, M.
2012 IEEE International Symposium on Circuits and Systems (ISCAS), p702
Towards biologically realistic multi-compartment neuron model emulation in analog VLSI
Sebastian Millner, Andreas Hartel, Johannes Schemmel, Karlheinz Meier
ESANN2012 20th European Symposium on Artificial Neural Networks Bruges, Belgium, April 25-26-27
Is a 4-bit synaptic weight resolution enough? - Constraints on enabling spike-timing dependent plasticity in neuromorphic hardware
Thomas Pfeil, Tobias C. Potjans, Sven Schrader, Wiebke Potjans, Johannes Schemmel, Markus Diesmann, Karlheinz Meier
Frontiers in Neuroscience 6:90 (2012)
A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems
Daniel Brüderle, Mihai A. Petrovici, Bernhard Vogginger, Matthias Ehrlich, Thomas Pfeil, Sebastian Millner, Andreas Grübl, Karsten Wendt, Eric Müller and Marc-Olivier Schwartz, et al.
Biological Cybernetics
A common language for neuronal networks in software and hardware
Andrew Davison, Eilif Muller, Daniel Brüderle and Jens Kremkow
The Neuromorphic Engineer
Simulator-Like Exploration of Cortical Network Architectures with a Mixed-Signal VLSI System
Daniel Brüderle, Johannes Bill, Bernhard Kaplan, Jens Kremkow, Karlheinz Meier, Eric Müller and Johannes Schemmel
Proceedings of the 2010 IEEE International Symposium on Circuits and Systems (Copyright: IEEE)
Compensating inhomogeneities of neuromorphic VLSI devices via short-term synaptic plasticity
Johannes Bill, Klaus Schuch, Daniel Brüderle, Johannes Schemmel, Wolfgang Maass and Karlheinz Meier
Frontiers in Computational Neuroscience 4:129 (2010)
A Wafer-Scale Neuromorphic Hardware System for Large-Scale Neural Modeling
Johannes Schemmel, Daniel Brüderle, Andreas Grübl, Matthias Hock, Karlheinz Meier and Sebastian Millner
Proceedings of the 2010 IEEE International Symposium on Circuits and Systems (Copyright: IEEE)
A software framework for mapping neural networks to a wafer-scale neuromorphic hardware system
Matthias Ehrlich, Karsten Wendt, Lukas Zühl, Rene Schüffny, Daniel Brüderle, Eric Müller and Bernhard Vogginger
Proceedings of the 2010 Artificial Neural Networks and Intelligent Information Processing Conference (ANNIIP)
A VLSI Implementation of the Adaptive Exponential Integrate-and-Fire Neuron Model
Sebastian Millner, Andreas Grübl, Karlheinz Meier, Johannes Schemmel, Marc-Olivier Schwartz
Advances in Neural Information Processing Systems
High-Conductance States on a Neuromorphic Hardware System
Bernhard Kaplan, Daniel Brüderle, Johannes Schemmel and Karlheinz Meier
Proceedings of International Joint Conference on Neural Networks, Atlanta, Georgia, USA, June 14-19, 2009
Establishing a Novel Modeling Tool: A Python-based Interface for a Neuromorphic Hardware System
Daniel Brüderle, Eric Müller, Andrew Davison, Eilif Muller, Johannes Schemmel, Karlheinz Meier
Front. Neuroinform. 3:17 (2009)
A QoS Network Architecture to Interconnect Large-Scale VLSI Neural Networks
Stefan Philipp, Karlheinz Meier, Johannes Schemmel
In Proc. of the 2009 International Joint Conference on Neural Networks (IJCNN"2009), Atlanta, Georgia, USA, June 2009, pp. 2525-2532
PyNN: A Common Interface for Neuronal Network Simulators
Andrew P. Davison, Daniel Brüderle, Jochen M. Eppler, Jens Kremkow, Eilif Muller, Dejan A. Pecevski, Laurent Perrinet and Pierre Yger
Frontiers in Neuroinformatics 2:11 (2008)
Realizing Biological Spiking Network Models in a Configurable Wafer-Scale Hardware System
Johannes Fieres, Johannes Schemmel, Karlheinz Meier
Proceedings IJCNN2008, IEEE Press (2008)
Wafer-Scale Integration of Analog Neural Networks
Johannes Schemmel, Johannes Fieres, Karlheinz Meier
Proceedings IJCNN2008, IEEE Press (2008)
A Software Framework for Tuning the Dynamics of Neuromorphic Silicon Towards Biology
Daniel Bruederle, Andreas Gruebl, Karlheinz Meier, Eilif Mueller, and Johannes Schemmel
In Proc. of IWANN 2007, San Sebastián, Spain, June 2007, Springer LNCS 4507, pp. 479 - 486
Spike-frequency adapting neural ensembles: Beyond mean adaptation and renewal theories.
Eilif Muller, Lars Buesing, Johannes Schemmel, Karlheinz Meier
Neural Computation, 19, 2958-3010.
Modeling Synaptic Plasticity within Networks of Highly Accelerated I&F Neurons
Johannes Schemmel, Daniel Bruederle, Karlheinz Meier, Boris Ostendorf
Proceedings of the 2007 IEEE International Symposium on Circuits and Systems, New Orleans, USA
Interconnecting VLSI Spiking Neural Networks Using Isochronous Connections
Stefan Philipp, Andreas Grübl, Karlheinz Meier, Johannes Schemmel
In Proc. of the 9th International Work-Conference on Artificial Neural
Networks (IWANN"2007), San Sebastián, Spain, June 2007, Springer LNCS 4507,
pp. 471-478
A convolutional neural network tolerant of synaptic faults for low-power analog hardware
J. Fieres, J. Schemmel, K. Meier
Proceedings of 2nd IAPR International Workshop on ArtificialNeural Networks in Pattern Recognition (ANNPR 2006), Springer LectureNotes in Artificial Intelligence 4087, 122--132 (2006)
Training convolutional neural networks of threshold neurons suited for low-power hardware implementation
J. Fieres, J. Schemmel, K. Meier
Proceedings of the 2006 International Joint Conference onNeural Networks (IJCNN 2006), 21--28, IEEE Press (2006)
Implementing Synaptic Plasticity in a VLSI Spiking Neural Network Model
Johannes Schemmel, Andreas Gruebl, Karlheinz Meier, Eilif Mueller
Proceedings of the 2006 International Joint Conference on Neural Networks (IJCNN 2006), 1-6, IEEE Press (2006)
A Modular Framework for the Evolution of Circuits on Configurable Transistor Array Architectures
Martin Trefzer, Jörg Langeheine, Karlheinz Meier, Johannes Schemmel
Proc. of the first NASA/ESA Conference on Adaptive Hardware and Systems AHS2006, ISBN: 0-7695-2614-4, IEEE Press, pp. 32-39, 2006
Operational Amplifiers: An Example for Multi-Objective Optimization on an Analog Evolvable Hardware Platform
Martin Trefzer, Jörg Langeheine, Karlheinz Meier, Johannes Schemmel
In J. Manuel Moreno and Jordi Madrenas and Jordi Cosp, editors, Proc. of ICES 2005, 6th International Conference on Evolvable Systems, ISBN: 3-540-28736-1, LNCS 3637, Springer-Verlag, pp. 86-97, 2005
A Flexible Scheme for Adaptive Integration Time Control
A. Breidenassel, J. Schemmel, K. Meier
IEEE Sensors conference
Methods for Simulating High-Conductance States in Neural Microcircuits
Eilif Mueller, K. Meier, J. Schemmel
Brain Inspired Cognitive Systems BICS2004, University of Stirling, Scotland, UK, August 29 - September 1, 2004, in press
Edge of Chaos Computation in Mixed-Mode VLSI - A Hard Liquid
Felix Schuermann, Karlheinz Meier, Johannes Schemmel
A Platform for Parallel Operation of VLSI Neural Networks
J. Fieres, A. Grübl, S. Philipp, K. Meier, J. Schemmel, F. Schürmann
Brain Inspired Cognitive Systems BICS2004, University of Stirling, Scotland, UK, August 29 - September 1, 2004, in press
A New VLSI Model of Neural Microcircuits Including Spike Time Dependent Plasticity
J. Schemmel, K. Meier, Eilif Mueller
Proceedings of the 2004 International Joint Conference on Neural Networks IJCNN"04, Budapest, Hungray, July 25.-29., pp. 1711-1716, 2004, IEEE Press
On the Evolution of Analog Electronic Circuits Using Building Blocks on a CMOS FPTA
Jörg Langeheine, Martin Trefzer, Daniel Brüderle, Karlheinz Meier,
Proc. of the Genetic and Evolutionary Computation Conferene (GECCO 2004), ISBN: 3-540-22344-4, LNCS 3102 (part I), Springer-Verlag, pp. 1316-1327, 2004
Intrinsic Evolution of Digital-to-Analog Converters Using a CMOS FPTA Chip
Jörg Langeheine, Karlheinz Meier, Johannes Schemmel, Martin Trefzer
Proc. of the NASA/DoD Conference on Evolvable Hardware (EH2004) , ISBN: 0-7695-2145-2, IEEE Press, pp. 18-25, 2004
New Genetic Operators to Facilitate Understanding of Evolved Transistor Circuits
Martin Trefzer, Jörg Langeheine, Johannes Schemmel, Karlheinz Meier
Proc. of the NASA/DoD Conference on Evolvable Hardware (EH2004), ISBN: 0-7695-2145-2, IEEE Press, pp. 217-224, 2004
Training Fast Mixed-Signal Neural Networks for Data Classification
S.G. Hohmann, J. Fieres, K. Meier, J. Schemmel, T. Schmitz, F. Schürmann
Proceedings of the 2004 International Joint Conference on Neural Networks IJCNN"04, Budapest, Hungray, July 25.-29., pp. 2647-2652, 2004, IEEE Press
Evaluation of a Pneumatically Driven Tactile Stimulator Device for Vision Substitution During fMRI-Studies
Anne-Catherin Zappe, T. Maucher, K. Meier, C. Scheiber
Magnetic Resonance in Medicine 2003 (in press)
Interfacing Binary Networks to Multi-valued Signals
F. Schuermann, S. Hohmann, K. Meier, J. Schemmel
Proceed. of the ICANN/ICONIP 2003
Intrinsic Evolution of Analog Electronic Circuits Using a CMOS FPTA Chip
J. Langeheine, K. Meier, J. Schemmel
Proc. of the EUROGEN 2003, Barcelona, Spain
A Mixed-Mode Analog Neural Network using Current-Steering Synapses
J. Schemmel, S. Hohmann, K. Meier, F. Schuermann
publ. by Kluwer Analog Integrated Circuits and Signal Processing
Predicting Protein Cellular Localization Sites with a Hardware Analog Neural Network
S. G. Hohmann, J. Schemmel, F. Schürmann, K. Meier
Proc. of July 2003 Int. Joint Conf. on Neural Networks, Portland, Oregon, IEEE Press, 0-7803-7899-7, pages 381-386
Speeding Up Hardware Evolution: A Coprocessor for Evolutionary Algorithms
T. Schmitz, S. Hohmann, K. Meier, J. Schemmel, F. Schuermann
Towards an Artificial Neural Network Framework
F. Schürmann, S. Hohmann, J. Schemmel, K. Meier
2002 NASA/DoD Conference on Evolvable Hardware
Intrinsic Evolution of Quasi DC Solutions for Transistor Level Analog Electronic Circuits Using a CMOS FPTA
J. Langeheine, K-H. Meier, J. Schemmel
2002 NASA/DoD Conference on Evolvable Hardware
An Integrated Mixed-Mode Neural Network Architecture for Megasynaspe ANNs
J. Schemmel, F. Schürmann, S. Hohmann, K. Meier
World Congress of Computational Intelligence (WCC12002)
A Scalable Switched Capacitor Realization at the Resistive Fuse Network
J. Schemmel, K. Meier, M. Loose
Anal. integrated Circuits and Signal Processing, vol 32 les. 2, Kluwer Ac. Publ.
Exploring the Parameter Space of a Genetic Alorithm for Training an Analog Neural Network
S. Hohmann, J. Schemmel, F. Schürmann, K. Meier
Genetic and Evolutionary Computing Conference
A CMOS FPTA Chip for Hardware Evolution of Analog Electronic Circuits
J. Langeheine, J. Becker, S. Fölling, K. Meier, J. Schemmel
Proc. of the Evolvable Hardware Workshop 2001, Long Beach, CA, USA
Initial studies of a new VLSI field programmable transistor array
J. Langeheine, J. Becker, S. Fölling, K. Meier, J. Schemmel
4. Int. conf. on Evolvable Systems: From Biology to Hardware (ICES 2001)
A VLSI implementation of an analog neural network suited for genetic algorithms
Johannes Schemmel
Towards a silicon primordial soup: A fast approach to hardware evolution with a VLSI transistor array
J. Langeheine, S. Fölling, K. Meier, J. Schemmel
In Proc. of the 3rd International Conference on Evolvable Systems: From
Biology to Hardware (ICES2000)
The Heidelberg Tactile Vision Substitution System
T. Maucher, J. Schemmel, K. Meier
In Proc. of the 6. Int. Conference on Tactile Aids, Hearing Aids and
Cochlear Implants (ISAC2000), May 23-26, 2000, University of Exeter, UK
The Heidelberg Tactile Vision Substitution System
T. Maucher, J. Schemmel, K. Meier
In Proc. of the 7th International Conference on Computer Helping People with
Special Needs (ICCHP 2000), July 17-21, 2000, Karlsruhe, Germany
A 66 x 66 pixels analog edge detection array with digital readout
J. Schemmel, M. Loose, K. Meier
Proceedings of the 25. European Solid-State Circuits (1999) (Conference)
A Tactile Vision Substitution System (Ed. Academic Press, Boston) ISBN 0-12-379773-X
M. Loose et al.
Ed. Academic Press, Boston
Self-calibrating logarthmic CMOS image sensor with single chip camera functionality (ps.gz)
M. Loose, K. Meier, J. schemmel
CMOS Image sensor with logarithmic response and self calibrating fixed pattern noise correction Int. Sympos. on Electronic Image Capture and Publishing
M. Loose, K. Meier, J. Schemmel
A Camera with adaptive Photoreceptors for a tactile Vision Aid
M. Loose, K. Meier, J. Schemmel
A Camera with adaptive Photoreceptors in analog CMOS
M. Loose, K. Meier, J. Schemmel
Entwicklung einer Kamera mit adaptiven Photorezeptoren in analoger CMOS Technology
M. Loose, K. Meier, J. Schemmel
ISBN 3-540-1585-7, Springer Verlag
Electronic Vision(s) Group
