Probabilistic Numerics School 2023
9 videos • 3,468 views • by Tübingen Machine Learning
Presentations during the Spring School on Probabilistic Numerics (Numerical Algorithms for and as Machine Learning) from 27 to 29 March 2023.
1
Philipp Hennig - Probabilistic Numerics in 2023
Tübingen Machine Learning
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2
Roman Garnett - Bayesian Optimization
Tübingen Machine Learning
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3
Simo Särkkä - Probabilistic differential equation solving as Bayesian filtering and smoothing
Tübingen Machine Learning
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4
Nicholas Krämer - Practical Probabilistic Numerical Solvers
Tübingen Machine Learning
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5
Carl Henrik Ek - Modulated surrogate models for Bayesian Optimization
Tübingen Machine Learning
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6
Jon Cockayne - A Bayesian Conjugate Gradient Method
Tübingen Machine Learning
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7
Masha Naslidnyk - Robust estimation for Gaussian Processes and beyond
Tübingen Machine Learning
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8
Toni Karvonen - Two pitfalls in Gaussian process interpolation
Tübingen Machine Learning
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9
Emilia Magnani - Learning solution operators for partial differential equations with uncertainty
Tübingen Machine Learning
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