The Mathematics of Machine Learning

Co-founded by PRIN: Gradient flows, Optimal Transport and Metric Measure Structures, AFORS, CRCNSERC: Artificial Intelligence at the Interface of Chemistry and Mathematics

23 January 2023 - 27 January 2023

Invited Speakers

[table view]

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: Log-concave sampling
Talk: Log-concave sampling
Talk: Log-concave sampling
Talk: Log-concave sampling
Talk: Log-concave sampling

Cristina Cipriani

Technical University of Munich
Talk: A Mean-Field 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- Haker-Tannenbau scheme

Simone Milanesi

Talk: The BeMi Stardust: a Structured Ensemble of Binarized Neural Networks

Maurizio Parton

Università di Chieti-Pescara
Talk: Improving Performance in Neural Networks by Dendrites-Activated Connections

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