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The Yin-Yang dataset
v1v2 (latest)

The Yin-Yang dataset

Neuro Inspired Computational Elements Workshop (NICE), 2021
16 February 2021
Laura Kriener
Julian Goltz
Mihai A. Petrovici
    3DH
ArXiv (abs)PDFHTML

Papers citing "The Yin-Yang dataset"

14 / 14 papers shown
Causal pieces: analysing and improving spiking neural networks piece by piece
Causal pieces: analysing and improving spiking neural networks piece by piece
Dominik Dold
Philipp Christian Petersen
CML
423
2
0
18 Apr 2025
Ontologies in Design: How Imagining a Tree Reveals Possibilites and Assumptions in Large Language Models
Ontologies in Design: How Imagining a Tree Reveals Possibilites and Assumptions in Large Language ModelsInternational Conference on Human Factors in Computing Systems (CHI), 2025
Nava Haghighi
Sunny Yu
James Landay
Daniela Rosner
247
0
0
03 Apr 2025
Short-reach Optical Communications: A Real-world Task for Neuromorphic
  Hardware
Short-reach Optical Communications: A Real-world Task for Neuromorphic HardwareNeuro Inspired Computational Elements Workshop (NICE), 2024
E. Arnold
Eike-Manuel Edelmann
Alexander von Bank
Eric Müller
Laurent Schmalen
Johannes Schemmel
208
2
0
04 Dec 2024
Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic
  Computing
Genetic Motifs as a Blueprint for Mismatch-Tolerant Neuromorphic ComputingInternational Symposium on Circuits and Systems (ISCAS), 2024
T. Boccato
D. Zendrikov
N. Toschi
Giacomo Indiveri
282
0
0
25 Oct 2024
Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural
  Network Performance
Layer Ensemble Averaging for Improving Memristor-Based Artificial Neural Network Performance
Osama Yousuf
Brian D. Hoskins
Karthick Ramu
Mitchell Fream
W. A. Borders
...
M. Daniels
A. Dienstfrey
Jabez J. McClelland
Martin Lueker-Boden
Gina Adam
225
1
0
24 Apr 2024
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic
  Hardware
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware
Eric Müller
Moritz Althaus
E. Arnold
Philipp Spilger
Christian Pehle
Johannes Schemmel
295
11
0
30 Jan 2024
Gradient-based methods for spiking physical systems
Gradient-based methods for spiking physical systems
Julian Goltz
Sebastian Billaudelle
Laura Kriener
Luca Blessing
Christian Pehle
Eric Müller
Johannes Schemmel
Mihai A. Petrovici
AI4CE
165
3
0
29 Aug 2023
Event-based Backpropagation for Analog Neuromorphic Hardware
Event-based Backpropagation for Analog Neuromorphic Hardware
Christian Pehle
Luca Blessing
E. Arnold
Eric Müller
Johannes Schemmel
321
10
0
13 Feb 2023
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling
  on BrainScaleS-2
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2Neuro Inspired Computational Elements Workshop (NICE), 2022
Philipp Spilger
E. Arnold
Luca Blessing
Christian Mauch
Christian Pehle
Eric Müller
Johannes Schemmel
181
13
0
23 Dec 2022
Learning efficient backprojections across cortical hierarchies in real
  time
Learning efficient backprojections across cortical hierarchies in real time
Kevin Max
Laura Kriener
Garibaldi Pineda García
Thomas Nowotny
Ismael Jaras
Walter Senn
Mihai A. Petrovici
OOD
361
22
0
20 Dec 2022
Exact Gradient Computation for Spiking Neural Networks Through Forward
  Propagation
Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation
Jane Lee
Saeid Haghighatshoar
Amin Karbasi
320
1
0
18 Oct 2022
Robust and accelerated single-spike spiking neural network training with
  applicability to challenging temporal tasks
Robust and accelerated single-spike spiking neural network training with applicability to challenging temporal tasks
Luke Taylor
Andrew J. King
N. Harper
AAML
327
12
0
30 May 2022
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware
A Scalable Approach to Modeling on Accelerated Neuromorphic HardwareFrontiers in Neuroscience (Front. Neurosci.), 2022
Eric Müller
E. Arnold
O. Breitwieser
Milena Czierlinski
Arne Emmel
...
V. Karasenko
Mitja Kleider
Aron Leibfried
Christian Pehle
Johannes Schemmel
230
27
0
21 Mar 2022
Fast and energy-efficient neuromorphic deep learning with first-spike
  times
Fast and energy-efficient neuromorphic deep learning with first-spike timesNature Machine Intelligence (NMI), 2019
Julian Goltz
Laura Kriener
A. Baumbach
Sebastian Billaudelle
O. Breitwieser
...
Á. F. Kungl
Walter Senn
Johannes Schemmel
K. Meier
Mihai A. Petrovici
715
157
0
24 Dec 2019
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