Machine Learning for Parameter Identification, Mathematical Challenges in Theory and Applications

Organizers: Dinh Nho Hao and Peter Maass

Ord.	Authors	Title
1	J. Adler A. Ringh J. Karlsson	Convex Optimization for Inverse Problems Using Convolutional Neural Networks
2	J. Adler O. Verdier	What Can We Expect? Computable Upper Bounds to Machine Learning in Inverse Problems Using MCMC
3	D. N. Hao N. T. N. Oanh P. X. Thanh	Determination of the Initial Condition in Parabolic Equations
4	Y. C. Hernandez T. Boskamp P. Maass	Targeted NMF for Tumor Classification
5	E. Kobler T. Klatzer K. Hammernik T. Pock	Variational Networks: Connecting Variational Methods and Deep Learning
6	S. Lunz J. Adler O. Öktem C. Schönlieb	Learned CT Reconstruction and Segmentation
7	H. T. Nguyen P. Maass D. N. Hao	On a Mathematical Model of Lithium/Air Batteries
8	D. Otero I. Piotrowska-Kurczewski P. Maass	Inverse Problems in Designing New Materials

Minisymposium