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The Mathematics of Machine Learning
Cofounded by PRIN: Gradient flows, Optimal Transport and Metric Measure Structures, AFORS, CRC
NSERC: Artificial Intelligence at the Interface of Chemistry and Mathematics
23 January 2023  27 January 2023
Aims and Research Directions
Scientific Committee
Organizing Committee
List of Participants
Invited Speakers
Timetable
Documents
Invited Speakers
[table view]
Pages:
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Luigi Ambrosio
Scuola Normale Superiore
Talk:
Special seminar: On some variational problems involving functions with bounded Hessian
Lorenzo Bonasera
Università degli Studi di Pavia
Talk:
Optimal Shapelets Tree for Time Series Interpretable Classification
Giuseppe Carleo
École polytechnique fédérale de Lausanne (EPFL)
Talk:
Machine Learning for Quantum Physics
Talk:
Machine Learning for Quantum Physics
Talk:
Machine Learning for Quantum Physics
Talk:
Machine Learning for Quantum Physics
Ambra Catozzi
ambra.catozzi@unipr.it
Talk:
Biomedical image classification via dynamically early stopped artificial neural network
Sinho Chewi
Massachusetts Institute of Technology
Talk:
Logconcave sampling
Talk:
Logconcave sampling
Talk:
Logconcave sampling
Talk:
Logconcave sampling
Talk:
Logconcave sampling
Cristina Cipriani
Technical University of Munich
Talk:
A MeanField Optimal Control Approach to the Training of NeurODEs
Lorenzo Giambagli
University of Namur
Talk:
Spectral Learning in Feedforward Neural Networks
Ismael Medina
Goettingen University
Talk:
Can one solve optimal transport with a Wasserstein gradient flow? Revisiting the Angenent HakerTannenbau scheme
Simone Milanesi
Talk:
The BeMi Stardust: a Structured Ensemble of Binarized Neural Networks
Maurizio Parton
Università di ChietiPescara
Talk:
Improving Performance in Neural Networks by DendritesActivated Connections
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