61 citations · 137 across the 23 of their papers we have counts for
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Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations
Paul Stoewer, Achim Schilling, Andreas Maier +1
Cognitive maps are a proposed concept on how the brain efficiently organizes memories and retrieves context out of them. The entorhinal-hippocampal complex is heavily involved in e…
Conceptual Cognitive Maps Formation with Neural Successor Networks and Word Embeddings
Paul Stoewer, Achim Schilling, Andreas Maier +1
The human brain possesses the extraordinary capability to contextualize the information it receives from our environment. The entorhinal-hippocampal plays a critical role in this f…
Joint MR sequence optimization beats pure neural network approaches for spin-echo MRI super-resolution
Hoai Nam Dang, Vladimir Golkov, Thomas Wimmer +3
Current MRI super-resolution (SR) methods only use existing contrasts acquired from typical clinical sequences as input for the neural network (NN). In turbo spin echo sequences (T…
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages
Soroosh Tayebi Arasteh, Cristian David Rios-Urrego, Elmar Noeth +4
Parkinson's disease (PD) is a neurological disorder impacting a person's speech. Among automatic PD assessment methods, deep learning models have gained particular interest. Recent…
Word class representations spontaneously emerge in a deep neural network trained on next word prediction
Kishore Surendra, Achim Schilling, Paul Stoewer +2
How do humans learn language, and can the first language be learned at all? These fundamental questions are still hotly debated. In contemporary linguistics, there are two major sc…