2 citations · 2 across the 3 of their papers we have counts for
3 papers
Unlocking In-Context Learning for Natural Datasets Beyond Language Modelling
Jelena Bratulić, Sudhanshu Mittal, David T. Hoffmann +5
Large Language Models (LLMs) exhibit In-Context Learning (ICL), which enables the model to perform new tasks conditioning only on the examples provided in the context without updat…
Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning
Lukas AW Gemein, Robin T Schirrmeister, Joschka Boedecker +1
The brain's biological age has been considered as a promising candidate for a neurologically significant biomarker. However, recent results based on longitudinal magnetic resonance…
Deep Learning for micro-Electrocorticographic (μECoG) Data
Xi Wang, C. Alexis Gkogkidis, Robin T. Schirrmeister +6
Machine learning can extract information from neural recordings, e.g., surface EEG, ECoG and μECoG, and therefore plays an important role in many research and clinical applications…