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- Invariant theory for machine learning (Dustin Mixon, Ohio State and Soledad Villar, Johns Hopkins)
Radu Balan (University of Maryland)
Ben Blum-Smith (Johns Hopkins University)
Dan Edidin (University of Missouri)
Joseph Iverson (Iowa State University)
- Frames, Riesz bases, and related topics (Jorge Antezana, Univ. of Barcelona)
Akram Aldroubi (Vanderbilt University)
Marcin Bownik (University of Oregon)
Dae Gwan Lee (Pukyong National University)
Romanos Malikiosis (Aristotle University of Thessaloniki)
Felipe Marceca (Austrian Academy of Sciences)
- Machine learning meets computational imaging (Sara Fridovich-Keil, Georgia Tech and Mahdi Soltanolkotabi, University of Southern California)
Sara Fridovich-Keil (Stanford/Georgia Tech)
Reinhard Heckel (TUM)
Justin Romberg (Georgia Tech)
Zhizhen (Jane) Zhao (UIUC)
- Optimal frames and codes (Dustin Mixon, Ohio State and Matthew Fickus Air Force Institute of Technolog)
Igor Balla (Masaryk University)
John Jasper (Air Force Institute of Technology)
Emily King (Colorado State University)
Barbara Lewandowska (Jagiellonian University)
- Advances in Phase Retrieval (Lukas Liehr, Bar Ilan and Irina Shafkulovska, Univ. of Vienna)
Dan Edidin (University of Missouri)
Philippe Jaming (University of Bordeaux)
Mitchell Taylor (ETH Zürich)
- Energy- and score-based models (Joakim Andén, KTH)
Erwan Allys (ENS)
Michael Elad (Technion)
Louis Grenioux (École polytechnique)
Sixin Zhang (INP-Toulouse)
- Unlimited Sensing (Ayush Bhandari, Imperial College London)
Ayush Bhandari (Imperial College London)
Geethu Joseph (Delft University of Technology)
Felix Krahmer (Technical University of Munich)
Mojtaba Soltanalian (University of Illinois at Chicago)
- Sampling and learning of deep neural networks (Philipp Petersen, Univ. Vienna)
Simone Brugiapaglia (Concordia University)
Martina Neuman (University of Vienna)
Felix Voigtlaender (Catholic University of Eichstätt-Ingolstadt)
Jakob Zech (Heidelberg University)