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Patrick Krauss
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2020 – today
- 2024
- [j10]Alina Schüller, Achim Schilling, Patrick Krauss, Tobias Reichenbach:
The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions. J. Cogn. Neurosci. 36(3): 475-491 (2024) - [j9]Claus Metzner, Marius E. Yamakou, Dennis Voelkl, Achim Schilling, Patrick Krauss:
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks. Neural Comput. 36(3): 351-384 (2024) - [j8]Achim Schilling
, Richard Gerum
, Claudia Boehm, Jwan Rasheed, Claus Metzner, Andreas Maier, Caroline Reindl, Hajo M. Hamer
, Patrick Krauss
:
Deep learning based decoding of single local field potential events. NeuroImage 297: 120696 (2024) - [i16]Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss:
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations. CoRR abs/2401.01364 (2024) - [i15]Patrick Krauss, Jannik Hösch, Claus Metzner, Andreas K. Maier, Peter Uhrig, Achim Schilling:
Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT. CoRR abs/2405.02024 (2024) - [i14]Linda-Sophie Schneider, Patrick Krauss, Nadine Schiering, Christopher Syben, Richard Schielein, Andreas Maier:
Data-driven Modeling in Metrology - A Short Introduction, Current Developments and Future Perspectives. CoRR abs/2406.16659 (2024) - 2023
- [c4]Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss:
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. ICDL 2023: 391-395 - [c3]Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas Maier, Patrick Krauss:
Word class representations spontaneously emerge in a deep neural network trained on next word prediction. ICMLA 2023: 1481-1486 - [c2]Richard Gerum
, André Erpenbeck, Patrick Krauss, Achim Schilling:
Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology. IJCNN 2023: 1-9 - [i13]Claus Metzner, Marius E. Yamakou, Dennis Voelkl, Achim Schilling, Patrick Krauss:
Quantifying and maximizing the information flux in recurrent neural networks. CoRR abs/2301.12892 (2023) - [i12]Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas K. Maier, Patrick Krauss:
Word class representations spontaneously emerge in a deep neural network trained on next word prediction. CoRR abs/2302.07588 (2023) - [i11]Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss:
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. CoRR abs/2307.01577 (2023) - [i10]Claus Metzner, Achim Schilling, Patrick Krauss:
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD). CoRR abs/2311.16621 (2023) - 2022
- [j7]Claus Metzner, Patrick Krauss:
Dynamics and Information Import in Recurrent Neural Networks. Frontiers Comput. Neurosci. 16: 876315 (2022) - [i9]Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas K. Maier, Patrick Krauss:
Neural Network based Successor Representations of Space and Language. CoRR abs/2202.11190 (2022) - [i8]Achim Schilling, William Sedley, Richard Gerum, Claus Metzner, Konstantin Tziridis, Andreas K. Maier, Holger Schulze, Fan-Gang Zeng, Karl J. Friston, Patrick Krauss:
Predictive Coding and Stochastic Resonance: Towards a Unified Theory of Auditory (Phantom) Perception. CoRR abs/2204.03354 (2022) - [i7]Claus Metzner, Achim Schilling, Maximilian Traxdorf, Konstantin Tziridis, Holger Schulze, Patrick Krauss:
Classification at the Accuracy Limit - Facing the Problem of Data Ambiguity. CoRR abs/2206.01922 (2022) - [i6]Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss:
Neural Network based Formation of Cognitive Maps of Semantic Spaces and the Emergence of Abstract Concepts. CoRR abs/2210.16062 (2022) - 2021
- [j6]Achim Schilling
, Andreas Maier, Richard Gerum, Claus Metzner
, Patrick Krauss
:
Quantifying the separability of data classes in neural networks. Neural Networks 139: 278-293 (2021) - [c1]Zijin Yang, Achim Schilling, Andreas Maier, Patrick Krauss:
Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data. Bildverarbeitung für die Medizin 2021: 211-216 - [i5]Andreas Maier, Harald Köstler, Marco Heisig, Patrick Krauss, Seung Hee Yang:
Known Operator Learning and Hybrid Machine Learning in Medical Imaging - A Review of the Past, the Present, and the Future. CoRR abs/2108.04543 (2021) - 2020
- [j5]Patrick Krauss, Andreas Maier:
Will We Ever Have Conscious Machines? Frontiers Comput. Neurosci. 14: 556544 (2020) - [j4]Richard C. Gerum
, André Erpenbeck
, Patrick Krauss
, Achim Schilling
:
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. Neural Networks 128: 305-312 (2020) - [i4]Patrick Krauss
, Andreas Maier:
Will we ever have Conscious Machines? CoRR abs/2003.14132 (2020)
2010 – 2019
- 2019
- [j3]Patrick Krauss
, Alexandra Zankl, Achim Schilling
, Holger Schulze, Claus Metzner:
Analysis of Structure and Dynamics in Three-Neuron Motifs. Frontiers Comput. Neurosci. 13: 5 (2019) - [j2]Patrick Krauss
, Karin Prebeck, Achim Schilling
, Claus Metzner:
Recurrence Resonance" in Three-Neuron Motifs. Frontiers Comput. Neurosci. 13: 64 (2019) - [i3]Richard C. Gerum, André Erpenbeck, Patrick Krauss
, Achim Schilling:
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. CoRR abs/1911.10988 (2019) - 2018
- [i2]Achim Schilling, Jonas Rietsch, Richard Gerum, Holger Schulze, Claus Metzner, Patrick Krauss
:
How deep is deep enough? - Optimizing deep neural network architecture. CoRR abs/1811.01753 (2018) - 2017
- [j1]Patrick Krauss
, Holger Schulze, Claus Metzner:
A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals. Artif. Life 23(4) (2017) - 2015
- [i1]Patrick Krauss
, Claus Metzner, Konstantin Tziridis, Holger Schulze:
Adaptive stochastic resonance based on output autocorrelations. CoRR abs/1504.05032 (2015)
Coauthor Index
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last updated on 2024-08-03 21:13 CEST by the dblp team
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