HU

MIA 2023

Mathematics and Image Analysis

1-3 February 2023, Berlin, Germany

General Information Conference Program Registration Conference Location PhD Prize
Conference Program
Below are the titles and the abstracts of the talks (click on the title to read the abstract).

The full program (time schedule, abstracts and poster titles) can be also downloaded from here.
Wednesday, 1 February

08:00-08:45
Registration
08:45-09:00
Welcome message
09:00-09:45
Tatiana Bubba, Deeply learned regularization for limited angle computed tomography
09:45-10:30
Julia Schnabel, AI-enabled medical imaging
10:30-11:00 Coffee Break
11:00-11:45
Mathieu Aubry, Analysis by synthesis for interpretable image collection analysis
11:45-12:30
Gloria Haro, Faces and voices: leveraging visual information for speech and singing voice applications
12:30-14:00 Lunch Break
14:00-14:45
Michael Arbel, Annealed flow transport Monte Carlo
14:45-15:30
Laetitia Chapel, Unbalanced optimal transport: efficient solutions for outlier-robust ML
15:30-16:00 Coffee Break
16:00-17:30 Poster Pitch
Thursday, 2 February

09:00-09:45
Florial Knoll, Machine learning for inverse problems in MR image reconstruction
09:45-10:30
Martin Burger, From optimization to sampling in imaging: A unified view based on coupling techniques
10:30-11:00 Coffee Break
11:00-11:45
Otmar Scherzer, Inverse problems for acoustic attenuating media
11:45-12:30
Audrey Repetti, A distributed Gibbs sampler for image recovery
12:30-14:00 Lunch Break
14:00-14:45
Ulugbek Kamilov, Plug-and-Play methods for integrating physical and learned models in computational imaging
14:45-15:30
Pierre Weiss, Training neural networks on families of operators
15:30-16:00 Coffee Break
16:00-16:45
Tom Goldstein, Solving neural inverse problems with diffusion models
16:45-18:30 Poster Session
Friday, 3 February

09:00-09:45
PhD Prize talk: Sebastian Neumayer, Learning convex regularizers: Does depth really help?
09:45-10:30
Tomer Michaeli, The implicit bias of SGD: A Minima stability analysis
10:30-11:00 Coffee Break
11:00-11:45
Nelly Pustelnik, On strong convexity for the understanding and design of (unfolded) algorithms
11:45-12:30
Serena Morigi, Image decomposition into structure, harmonic and oscillatory components
12:30-14:00 Lunch Break
14:00-14:45
Zorah Lähner, Intrinsic neural fields: Learning functions on manifolds
14:45-15:30
Vladimir Spokoiny, Bayesian inference for complex models
15:30-16:00 Closing Remarks
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