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2020 – today
- 2025
[j10]Pegah Ramezani, Achim Schilling, Patrick Krauss:
Analysis of argument structure constructions in the large language model BERT. Frontiers Artif. Intell. 8 (2025)- [j9]Paul Stoewer, Achim Schilling, Pegah Ramezani, Hassane Kissane, Andreas K. Maier, Patrick Krauss
:
Multi-modal cognitive maps for language and vision based on neural successor representations. Neurocomputing 631: 129662 (2025) - [i22]Awritrojit Banerjee, Achim Schilling, Patrick Krauss:
Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT. CoRR abs/2501.08053 (2025) - [i21]Fabian Hildebrandt, Andreas K. Maier, Patrick Krauss, Achim Schilling:
Refusal Behavior in Large Language Models: A Nonlinear Perspective. CoRR abs/2501.08145 (2025) - [i20]Patrick Krauss, Achim Schilling:
Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions. CoRR abs/2501.10072 (2025) - [i19]Hassane Kissane, Achim Schilling, Patrick Krauss:
Probing Internal Representations of Multi-Word Verbs in Large Language Models. CoRR abs/2502.04789 (2025) - 2024
- [j8]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) - [j7]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) - [j6]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) - [c5]Nikola Kölbl, Konstantin Tziridis, Patrick Krauss, Achim Schilling:
Methodological Considerations in the Analysis of Acoustically Evoked Neural Signals: A Comparative Study of Active EEG, Passive EEG and MEG. EMBC 2024: 1-7 - [i18]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) - [i17]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) - [i16]Pegah Ramezani, Achim Schilling, Patrick Krauss:
Analysis of Argument Structure Constructions in a Deep Recurrent Language Model. CoRR abs/2408.03062 (2024) - [i15]Pegah Ramezani, Achim Schilling, Patrick Krauss:
Analysis of Argument Structure Constructions in the Large Language Model BERT. CoRR abs/2408.04270 (2024) - [i14]Claus Metzner, Achim Schilling, Andreas K. Maier, Patrick Krauss:
Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing. CoRR abs/2411.10047 (2024) - [i13]Mathis Immertreu, Achim Schilling, Andreas Maier, Patrick Krauss:
Probing for Consciousness in Machines. CoRR abs/2411.16262 (2024) - [i12]Hassane Kissane, Achim Schilling, Patrick Krauss:
Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT. CoRR abs/2412.14670 (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 - [i11]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) - [i10]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) - [i9]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) - [i8]Claus Metzner, Achim Schilling, Patrick Krauss:
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD). CoRR abs/2311.16621 (2023) - 2022
- [i7]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) - [i6]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) - [i5]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) - [i4]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
- [j5]Richard C. Gerum, Achim Schilling:
Integration of Leaky-Integrate-and-Fire Neurons in Standard Machine Learning Architectures to Generate Hybrid Networks: A Surrogate Gradient Approach. Neural Comput. 33(10): 2827-2852 (2021) - [j4]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 - 2020
- [j3]Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling:
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. Neural Networks 128: 305-312 (2020) - [i3]Richard C. Gerum, Achim Schilling:
Spiking Machine Intelligence: What we can learn from biology and how spiking Neural Networks can help to improve Machine Learning. CoRR abs/2004.13532 (2020)
2010 – 2019
- 2019
- [j2]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) - [j1]Patrick Krauss, Karin Prebeck, Achim Schilling, Claus Metzner:
Recurrence Resonance" in Three-Neuron Motifs. Frontiers Comput. Neurosci. 13: 64 (2019) - [i2]Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling:
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. CoRR abs/1911.10988 (2019) - 2018
- [i1]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)
Coauthor Index
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