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- KAUST
- Google Scholar
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Check out our new book on ‘Bayesian Deep Learning’
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Our new “Handbook of Bayesian Deep Learning” is now available online (link)
Talk at ISBA ‘Model Selection for Over-Parameterized Models’
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Invited talk at the ‘Calibrated Bayes: Model Design and Adaptation Under Limited Resources’ session at ISBA in Nagoya: “Model Selection for Over-Parameterized Models” (link)
Paper ‘Review of timescale distributions for electrochemical impedance spectroscopy analysis: Advantages, synergies, and future directions’ accepted in DeCarbon
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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)
Check out our new paper ‘DIPHINE: Diffusion-based Φ-ID Neural Estimator’ (link)
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Check out our new paper “DIPHINE: Diffusion-based Φ-ID Neural Estimator” (link)