Achim Schilling

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Avoid Overfitting

Machine Learning

Top Venues

Frontiers Comput. Neurosci.

Neural Networks

Publications

Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations. CoRR (2024)
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 (2024)
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) (2024)
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) (2024)
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 (2024)
Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. CoRR (2023)
Claus Metzner, Achim Schilling, Patrick Krauss
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD). CoRR (2023)
Paul Stoewer, Achim Schilling, Andreas K. Maier, Patrick Krauss
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings. ICDL (2023)
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)
Claus Metzner, Marius E. Yamakou, Dennis Voelkl, Achim Schilling, Patrick Krauss
Quantifying and maximizing the information flux in recurrent neural networks. CoRR (2023)
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)
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 (2023)
Claus Metzner, Achim Schilling, Maximilian Traxdorf, Konstantin Tziridis, Holger Schulze, Patrick Krauss
Classification at the Accuracy Limit - Facing the Problem of Data Ambiguity. CoRR (2022)
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 (2022)
Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas K. Maier, Patrick Krauss
Neural Network based Successor Representations of Space and Language. CoRR (2022)
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 (2022)
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)
Achim Schilling, Andreas Maier, Richard Gerum, Claus Metzner, Patrick Krauss
Quantifying the separability of data classes in neural networks. Neural Networks 139 (2021)
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) (2021)
Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. Neural Networks 128 (2020)
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 (2020)
Richard C. Gerum, André Erpenbeck, Patrick Krauss, Achim Schilling
Sparsity through evolutionary pruning prevents neuronal networks from overfitting. CoRR (2019)
Patrick Krauss, Alexandra Zankl, Achim Schilling, Holger Schulze, Claus Metzner
Analysis of Structure and Dynamics in Three-Neuron Motifs. Frontiers Comput. Neurosci. 13 (2019)
Patrick Krauss, Karin Prebeck, Achim Schilling, Claus Metzner
Recurrence Resonance" in Three-Neuron Motifs. Frontiers Comput. Neurosci. 13 (2019)
Achim Schilling, Jonas Rietsch, Richard Gerum, Holger Schulze, Claus Metzner, Patrick Krauss
How deep is deep enough? - Optimizing deep neural network architecture. CoRR (2018)