Large-Scale Experiments on Wafer-Scale Neuromorphic Hardware
Hartmut Schmidt
HD-KIP 24-64
Interconnect technologies for very large spiking neural networks
Tobias Thommes
HD-KIP 23-101
From transistors to learning systems: circuits and algorithms for brain-inspired computing
Sebastian Billaudelle
HD-KIP 22-91
From microscopic dynamics to ensemble behavior in spiking neural networks
Andreas Baumbach
HD-KIP 21-05
Operating Accelerated Neuromorphic Hardware - A Scalable and Sustainable Approach
Christian Paul Mauch
HD-KIP 21-08
Adjoint equations of spiking neural networks
Christian Pehle
HD-KIP 21-106
Accelerated neuromorphic cybernetics
Korbinian Schreiber
HD-KIP 21-14
Learning by Tooling: Novel Neuromorphic Learning Strategies in Reproducible Software Environments
Oliver Julien Breitwieser
HD-KIP 21-78
Robust learning algorithms for spiking and rate-based neural networks
Akos F. Kungl
HD-KIP 20-63
Harnessing function from form: towards bio-inspired artificial intelligence in neuronal substrates
Dold, Dominik
HD-KIP 21-16
Von Neumann bottlenecks in non-von Neumann computing architectures
Vitali Karasenko
HD-KIP 20-107
Solving machine learning problems with biological principles
Luziwei Leng
HD-KIP 19-83
Mixed-Signal Circuit Implementation of Spiking Neuron Models
Syed Ahmed Aamir
HD-KIP 18-51
Device Variability in Synapses of Neuromorphic Circuits
Christoph Koke
HD-KIP 17-23
Achieving a Higher Integration Level of Neuromorphic Hardware using Wafer Embedding
Gilbert Maurice Güttler
HD-KIP 17-129
Computing with noise in spiking neural networks
Ilja Bytschok
HD-KIP 17-54
Neuron Circuit Characterization in a Neuromorphic System
Mitja Kleider
HD-KIP 17-135
Modeling and Verification for a Scalable Neuromorphic Substrate
Paul Müller
HD-KIP 17-119
Implementation and Characterization of Mixed-Signal Neuromorphic ASICs
Hartel, Andreas
HD-KIP 16-07
Form vs. Function - Theory and Models for Neuronal Substrates
Mihai A. Petrovici
HD-KIP 15-60
Exploring the potential of brain-inspired computing
Thomas Pfeil
HD-KIP 15-18
Novel Operation Modes of Accelerated Neuromorphic Hardware
Eric Christian Müller
HD-KIP 14-98
Modern semiconductor technologies for neuromorphic hardware
Matthias Hock
HD-KIP 14-105
A Scalable Workflow for a Configurable
Neuromorphic Platform
Sebastian Jeltsch
HD-KIP 14-51
A new approach to learning in neuromorphic hardware
Friedmann, Simon
HD-KIP 13-86
Reproducing Biologically Realistic Regimes on a Highly-Accelerated Neuromorphic Hardware System
Marc-Olivier Schwartz
HD-KIP 13-87
Development of a Multi-Compartment Neuron Model Emulation
Sebastian Millner
HD-KIP 12-83
Neuroscientific Modeling with a Mixed-Signal VLSI Hardware System
Daniel Brüderle
HD-KIP 09-30
Design and Implementation of a Multi-Class Network Architecture for Hardware Neural Networks
Stefan Philipp
HD-KIP 08-20
VLSI Implementation of a Spiking Neural Network
Andreas Grübl
HD-KIP 07-10
Markov Process Models for Neural Ensembles with Spike-Frequency Adaptation
Eilif Benjamin Muller
HD-KIP 06-17
A Method for Image Classification Using Low-Precision Analog Computing Arrays
Johannes Fieres
HD-KIP 06-20
Evolution of Transistor Circuits
Martin Trefzer
HD-KIP 06-29
Evolution in Hardware - Eine Experimentalplattform zum parallelen Training analoger neuronaler Netzwerke
Tillmann Schmitz
HD-KIP 06-18
A High Dynamic Range CMOS Image Sensor with Adaptive Integration Time Control
Andreas Breidenassel
HD-KIP 05-06
Exploring Liquid Computing in a Hardware Adaptation: Construction and Operation of a Neural Network Experiment
Felix Schürmann
HD-KIP 05-09
Intrinsic Hardware Evolution on the Transistor Level
Joerg Langeheine
HD-KIP 05-12
Stepwise Evolutionary Training Strategies for Hardware Neural Networks
Steffen Hohmann
HD-KIP 05-05
Untersuchung der durch taktile Muster evozierten Änderungen der Aktivität im Cortex mit einem pneumatischen Display
Thorsten Maucher
HD-KIP 04-17
Magnetic source imaging of tactile evoked activity in the human secondary somatosensory cortex
Karsten Hoechstetter
HD-KIP 01-13
An Integrated Analog Network for Image Processing
Johannes Schemmel
IHEP 99-08
A Self Calibrating CMOS Image Sensor with Logarithmic Response
Markus Loose
IHEP 99-07
Electronic Vision(s) Group – Dr. Johannes Schemmel
Im Neuenheimer Feld 227
69120 Heidelberg
Germany
phone: +49 6221 549849
fax: +49 6221 549839
email: schemmel(at)kip.uni-heidelberg.de
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