New research: Dang & Valkonen - Leak localisation with a measure source convection–diffusion model

https://arxiv.org/abs/2605.12095

#inverseproblems
#optimisation

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Optimal estimation (Remote sensing 🛰️)

In applied statistics, optimal estimation is a regularized matrix inverse method based on Bayes' theorem. It is used very commonly in the geosciences, particularly for atmospheric sounding. A matrix inverse problem looks like this: A x → = y → {\displaystyle \mathbf {A} {\vec {x}}={\vec {y}}} The essential concept is to transform the matrix, A, into a c...

https://en.wikipedia.org/wiki/Optimal_estimation

#OptimalEstimation #RemoteSensing #InverseProblems

Did you know a CT scan uses math to create images from X-ray data? 🤔 Prof. Martin Burger and Samira Kabri from our Research Unit at @DESYnews shared how #inverseproblems turn data into images during "Wir wollen’s wissen" at Hamburg schools. Inspiring future scientists! 💡

@unihh #science #STEMEducation #ScienceOutreach

Morgen zu Gast um 16:15 im Sitzungszimmer des Mathematischen Instituts für das #RTG2491Kolloquium :
Angkana Rüland von der Universität Bonn mit
"On (In-)Stability Mechanisms in Inverse Problems"

#InverseProblems

🔊 Join us for the "#DeepLearning in #InverseProblems" Workshop on 23-24/9/24 at @DESYnews!

Explore the latest in learning-based methods for inverse problems with top experts.

Register by 15/9 👉 http://indico.desy.de/event/45763/

Don't miss out on this opportunity to expand your skills!