2 citations · 2 across the 2 of their papers we have counts for
3 papers
What Neuroscience Can Teach AI About Learning in Continuously Changing Environments
Daniel Durstewitz, Bruno Averbeck, Georgia Koppe
Modern AI models, such as large language models, are usually trained once on a huge corpus of data, potentially fine-tuned for a specific task, and then deployed with fixed paramet…
dsLassoCov: a federated machine learning approach incorporating covariate control
Han Cao, Augusto Anguita, Charline Warembourg +8
Machine learning has been widely adopted in biomedical research, fueled by the increasing availability of data. However, integrating datasets across institutions is challenging due…
A scalable generative model for dynamical system reconstruction from neuroimaging data
Eric Volkmann, Alena Brändle, Daniel Durstewitz +1
Data-driven inference of the generative dynamics underlying a set of observed time series is of growing interest in machine learning and the natural sciences. In neuroscience, such…