Participating in the Dagstuhl seminar Differential Equations and Continuous-Time Deep Learning organ

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Published: August 15, 2022

Participating in the Dagstuhl seminar Differential Equations and Continuous-Time Deep Learning organized by M. Welling, D. Duvenaud, M. Heinonen and M. Tiemann (link)

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Check out our new book on ‘Bayesian Deep Learning’

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Published: August 25, 2026

Our new “Handbook of Bayesian Deep Learning” is now available online (link)

Talk at the SMILES summer schools ‘Bayesian Deep Learning’

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Talk at ISBA ‘Model Selection for Over-Parameterized Models’

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Published: July 02, 2026

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Paper ‘Review of timescale distributions for electrochemical impedance spectroscopy analysis: Advantages, synergies, and future directions’ accepted in DeCarbon

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Published: June 18, 2026

Our paper “Review of timescale distributions for electrochemical impedance spectroscopy analysis: Advantages, synergies, and future directions” has been accepted for publication in the journal DeCarbon (link)

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