Achim Schilling

Orcid: 0000-0001-9543-305X

According to our database1, Achim Schilling authored at least 20 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Quantifying and Maximizing the Information Flux in Recurrent Neural Networks.
Neural Comput., March, 2024

The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions.
J. Cogn. Neurosci., March, 2024

Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT.
CoRR, 2024

Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations.
CoRR, 2024

2023
Beyond Labels: Advancing Cluster Analysis with the Entropy of Distance Distribution (EDD).
CoRR, 2023

Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology.
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.
Proceedings of the International Conference on Machine Learning and Applications, 2023

Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings.
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.
CoRR, 2022

Classification at the Accuracy Limit - Facing the Problem of Data Ambiguity.
CoRR, 2022

Predictive Coding and Stochastic Resonance: Towards a Unified Theory of Auditory (Phantom) Perception.
CoRR, 2022

Neural Network based Successor Representations of Space and Language.
CoRR, 2022

2021
Quantifying the separability of data classes in neural networks.
Neural Networks, 2021

Integration of Leaky-Integrate-and-Fire Neurons in Standard Machine Learning Architectures to Generate Hybrid Networks: A Surrogate Gradient Approach.
Neural Comput., 2021

Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data.
Proceedings of the Bildverarbeitung für die Medizin 2021, 2021

2020
Sparsity through evolutionary pruning prevents neuronal networks from overfitting.
Neural Networks, 2020

Spiking Machine Intelligence: What we can learn from biology and how spiking Neural Networks can help to improve Machine Learning.
CoRR, 2020

2019
Analysis of Structure and Dynamics in Three-Neuron Motifs.
Frontiers Comput. Neurosci., 2019

Recurrence Resonance" in Three-Neuron Motifs.
Frontiers Comput. Neurosci., 2019

2018
How deep is deep enough? - Optimizing deep neural network architecture.
CoRR, 2018


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