Achim Schilling

According to our database, Achim Schilling authored at least 30 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Author-Specific Linguistic Patterns Unveiled: A Deep Learning Study on Word Class Distributions.

Patrick Krauss, Achim Schilling

CoRR, January, 2025

Refusal Behavior in Large Language Models: A Nonlinear Perspective.

Fabian Hildebrandt, Andreas K. Maier, Patrick Krauss, Achim Schilling

CoRR, January, 2025

Exploring Narrative Clustering in Large Language Models: A Layerwise Analysis of BERT.

Awritrojit Banerjee, Achim Schilling, Patrick Krauss

CoRR, January, 2025

2024

Quantifying and Maximizing the Information Flux in Recurrent Neural Networks.

Claus Metzner, Marius E. Yamakou, Dennis Voelkl, Achim Schilling, Patrick Krauss

Neural Comput., March, 2024

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

Alina Schüller, Achim Schilling, Patrick Krauss, Tobias Reichenbach

J. Cogn. Neurosci., March, 2024

Deep learning based decoding of single local field potential events.

Achim Schilling, Richard Gerum, Claudia Boehm, Jwan Rasheed, Claus Metzner, Andreas Maier, Caroline Reindl, Hajo M. Hamer, Patrick Krauss

NeuroImage, 2024

Analysis and Visualization of Linguistic Structures in Large Language Models: Neural Representations of Verb-Particle Constructions in BERT.

Hassane Kissane, Achim Schilling, Patrick Krauss

CoRR, 2024

Probing for Consciousness in Machines.

Mathis Immertreu, Achim Schilling, Andreas Maier, Patrick Krauss

CoRR, 2024

Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing.

Claus Metzner, Achim Schilling, Andreas K. Maier, Patrick Krauss

CoRR, 2024

Analysis of Argument Structure Constructions in the Large Language Model BERT.

Pegah Ramezani, Achim Schilling, Patrick Krauss

CoRR, 2024

Analysis of Argument Structure Constructions in a Deep Recurrent Language Model.

Pegah Ramezani, Achim Schilling, Patrick Krauss

CoRR, 2024

Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT.

Patrick Krauss, Jannik Hösch, Claus Metzner, Andreas K. Maier, Peter Uhrig, Achim Schilling

CoRR, 2024

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

Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss

CoRR, 2024

Methodological Considerations in the Analysis of Acoustically Evoked Neural Signals: A Comparative Study of Active EEG, Passive EEG and MEG.

Nikola Kölbl, Konstantin Tziridis, Patrick Krauss, Achim Schilling

Proceedings of the 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2024

2023

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

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.

Richard Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling

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.

Kishore Surendra, Achim Schilling, Paul Stoewer, Andreas Maier, Patrick Krauss

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

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

Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss

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

2022

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

Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss

CoRR, 2022

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

Claus Metzner, Achim Schilling, Maximilian Traxdorf, Konstantin Tziridis, Holger Schulze, Patrick Krauss

CoRR, 2022

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

Achim Schilling, William Sedley, Richard Gerum, Claus Metzner, Konstantin Tziridis, Andreas K. Maier, Holger Schulze, Fan-Gang Zeng, Karl J. Friston, Patrick Krauss

CoRR, 2022

Neural Network based Successor Representations of Space and Language.

Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas K. Maier, Patrick Krauss

CoRR, 2022

2021

Quantifying the separability of data classes in neural networks.

Achim Schilling, Andreas Maier, Richard Gerum, Claus Metzner, Patrick Krauss

Neural Networks, 2021

Integration of Leaky-Integrate-and-Fire Neurons in Standard Machine Learning Architectures to Generate Hybrid Networks: A Surrogate Gradient Approach.

Richard C. Gerum, Achim Schilling

Neural Comput., 2021

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

Zijin Yang, Achim Schilling, Andreas Maier, Patrick Krauss

Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020

Sparsity through evolutionary pruning prevents neuronal networks from overfitting.

Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling

Neural Networks, 2020

Spiking Machine Intelligence: What we can learn from biology and how spiking Neural Networks can help to improve Machine Learning.

Richard C. Gerum, Achim Schilling

CoRR, 2020

2019

Analysis of Structure and Dynamics in Three-Neuron Motifs.

Patrick Krauss, Alexandra Zankl, Achim Schilling, Holger Schulze, Claus Metzner

Frontiers Comput. Neurosci., 2019

Recurrence Resonance" in Three-Neuron Motifs.

Patrick Krauss, Karin Prebeck, Achim Schilling, Claus Metzner

Frontiers Comput. Neurosci., 2019

2018

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

Achim Schilling, Jonas Rietsch, Richard Gerum, Holger Schulze, Claus Metzner, Patrick Krauss

CoRR, 2018