Jannis Schuecker

Fraunhofer Institute for Machine Tools and Forming Technology — Germany

Neuroscience · Life Sciences

8h-index924citations25works0.02yr avg
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Research Topics

Neural dynamics and brain function(11), stochastic dynamics and bifurcation(9), Neural Networks and Applications(8), Model Reduction and Neural Networks(4), Nonlinear Dynamics and Pattern Formation(3)

Publications24 total

Combining expert knowledge and neural networks to model environmental\n stresses in agriculture
arXiv (Cornell University)·2021· 1 citedOpen Access
Combining expert knowledge and neural networks to model environmental stresses in agriculture
arXiv (Cornell University)·2021Open Access
Learning Deep Generative Models for Queuing Systems
Proceedings of the AAAI Conference on Artificial Intelligence·2021· 8 citedOpen Access
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems
IEEE Transactions on Knowledge and Data Engineering·2021· 755 citedOpen Access
Conditions for wave trains in spiking neural networks
Physical Review Research·2020· 25 citedOpen Access
Recurrent Point Processes for Dynamic Review Models
arXiv (Cornell University)·2019· 3 citedOpen Access
Auto-Encoding Explanatory Examples
2019
Patterns and Outliers in Temporal Point Processes
Advances in intelligent systems and computing·2019· 2 cited
Recurrent Adversarial Service Times
arXiv (Cornell University)·2019Open Access
[Re] A Neural Model Of The Saccade Generator In The Reticular Formation
Data Archiving and Networked Services (DANS)·2018Open Access
Conditions for traveling waves in spiking neural networks
arXiv (Cornell University)·2018· 10 citedOpen Access
SPSA for Layer-Wise Training of Deep Networks
Lecture notes in computer science·2018· 5 cited
26th Annual Computational Neuroscience Meeting (CNS*2017): Part 1
BMC Neuroscience·2017Open Access
Fundamental Activity Constraints Lead to Specific Interpretations of the Connectome
PLoS Computational Biology·2017· 35 citedOpen Access
Data from: Fundamental activity constraints lead to specific interpretations of the connectome
Data Archiving and Networked Services (DANS)·2017Open Access
Cortical correlations support optimal sequence memory
2017
Functional methods for disordered neural networks
arXiv (Cornell University)·2016· 12 citedOpen Access
Noise dynamically suppresses chaos in random neural networks
arXiv (Cornell University)·2016· 3 citedOpen Access
Noise dynamically suppresses chaos in neural networks
arXiv (Cornell University)·2016· 8 citedOpen Access
Identifying and exploiting the anatomical origin of population rate oscillations in multi-layered spiking networks
BMC Neuroscience·2015Open Access
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Frequent Co-authors

Moritz Helias(14), Markus Diesmann(8), Christian Bauckhage(7), Kostadin Cvejoski(6), Bogdan Georgiev(5), Sven Goedeke(5), César Ojeda(4), Ramsés J. Sánchez(4), Maximilian Schmidt(2), Sacha J. van Albada(2), Johanna Senk(2), Karolína Korvasová(2), Espen Hagen(2), Tom Tetzlaff(2), David Dahmen(2), Anne‐Katrin Mahlein(2), Markus Diesmann(2), Laura von Rueden(1), Sebastian Mayer(1), Katharina Beckh(1)