Patrick Krauss

Orcid: 0000-0002-6611-7733

According to our database¹, Patrick Krauss authored at least 22 papers between 2015 and 2024.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

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Bibliography

2024

Quantifying and Maximizing the Information Flux in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Neural Comput., March, 2024

The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions.

[BibT_eX]

[DOI]

J. Cogn. Neurosci., March, 2024

Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD).

[BibT_eX]

[DOI]

Claus Metzner

Achim Schilling

Patrick Krauss

CoRR, 2023

Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2023

Word class representations spontaneously emerge in a deep neural network trained on next word prediction.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2023

Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Development and Learning, 2023

2022

Dynamics and Information Import in Recurrent Neural Networks.

[BibT_eX]

[DOI]

Claus Metzner

Patrick Krauss

Frontiers Comput. Neurosci., 2022

Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Concepts.

[BibT_eX]

[DOI]

CoRR, 2022

Classification at the Accuracy Limit - Facing the Problem of Data Ambiguity.

[BibT_eX]

[DOI]

CoRR, 2022

Predictive Coding and Stochastic Resonance: Towards a Unified Theory of Auditory (Phantom) Perception.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Network based Successor Representations of Space and Language.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Quantifying the separability of data classes in neural networks.

[BibT_eX]

[DOI]

Neural Networks, 2021

Known Operator Learning and Hybrid Machine Learning in Medical Imaging - A Review of the Past, the Present, and the Future.

[BibT_eX]

[DOI]

CoRR, 2021

Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

Sparsity through evolutionary pruning prevents neuronal networks from overfitting.

[BibT_eX]

[DOI]

Neural Networks, 2020

Will We Ever Have Conscious Machines?

[BibT_eX]

[DOI]

Patrick Krauss

Andreas Maier

Frontiers Comput. Neurosci., 2020

2019

Analysis of Structure and Dynamics in Three-Neuron Motifs.

[BibT_eX]

[DOI]

Frontiers Comput. Neurosci., 2019

Recurrence Resonance" in Three-Neuron Motifs.

[BibT_eX]

[DOI]

Frontiers Comput. Neurosci., 2019

2018

How deep is deep enough? - Optimizing deep neural network architecture.

[BibT_eX]

[DOI]

CoRR, 2018

2017

A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals.

[BibT_eX]

[DOI]

Patrick Krauss

Holger Schulze

Claus Metzner

Artif. Life, 2017

2015

Adaptive stochastic resonance based on output autocorrelations.

[BibT_eX]

[DOI]

CoRR, 2015

Patrick Krauss

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