Workshop
22 Aug, 2022 - 30 Sep, 2022
Machine learning (ML) is nowadays an important toolbox for theoretical and experimental physics, and its importance is expected to steadily grow in the coming years. Thanks to its effectiveness and extreme flexibility, it allows for applications covering a huge set of topics, ranging from statistical data analysis, to simulation and modeling. For this reason ML has been successfully used in very different research areas, such as high-energy physics, astrophysics and cosmology, condensed matter and statistical physics.
Applications in different domains often share strong similarities either in the problems to be solved or in the methodology employed. This motivates a fruitful exchange of ideas, which however is seldom achieved in practice due to the distance among different research communities.
The aim of the workshop is to bring together researchers with interests and expertise in ML from different fields in physics, strongly encouraging and promoting cross-topic exchange of ideas and collaborations. Three broad research areas will be covered:
- High-Energy Physics
- Astrophysics, Cosmology and Astroparticles
- Condensed Matter and Statistical Physics (including Quantum Information)
The distinctive trait of the workshop will be the focus on theoretical physics in a broad sense, including data analysis as well as simulation and modelling.
- Methods for regression and statistical analysis
- Monte Carlo integration and simulation
- Anomaly detection
- Classification
- Time series analysis
- Clustering and multi-dimensional visualization
- Equation solving
- Artificial intelligence-inspired and -augmented science
- Statistical physics algorithms for optimization and learning problems
- Quantum machine learning
Massimo Brescia (INAF Napoli)
Filippo Caruso (U. Firenze)
S. George Djorgovski (Caltech)
Duccio Fanelli (U. Firenze)
Alessandro Marconi (U. Firenze)
Florian Marquardt (Max Planck Erlangen)
Giuliano Panico (U. Firenze)
Jesse Thaler (MIT)
Andrea Wulzer (CERN & U. Padova)
Giuliano Panico (U. Firenze)
The participants who would like to present a poster are kindly invited to send an email with the title and a short abstract to alice.bernamonti@unifuit before May 22, specifying for which week of the workshop. Since a limited number of panels is available, the organizers will select the posters shortly after the deadline.
week 3
| Monday | Tuesday | Wednesday | Thursday | Friday | |
|---|---|---|---|---|---|
| 11:30 - 12:30 | Tomasevic | Newenfeld | Collin-Ellerin | Caceres | |
| 13:00 - 14:30 | lunch | lunch | lunch | lunch | lunch |
| 14:30 - 15:30 | Sorce | Emparan |
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| Date | Speaker | Title | Type | Useful Links |
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| 22 Aug, 2022 - 14:30-14:45 | Welcome | Introduction |
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| 22 Aug, 2022 - 14:45-16:15 | Gong show | Introduction |
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| 23 Aug, 2022 - 14:30-16:00 | Andrea Wulzer (Padova University) , Gaia Grosso (CERN) | Anomaly detection | Lecture |
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| 24 Aug, 2022 - 11:00-12:30 | Marco Letizia (University of Genova) | Efficient large scale kernel methods for high energy physics | Lecture |
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| 25 Aug, 2022 - 11:00-12:30 | Lorenzo Giambagli (University of Firenze) , Matilde Signorini (University of Firenze) | Non-parametric analysis of the Hubble Diagram with Neural Networks | Lecture |
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| 26 Aug, 2022 - 11:00-12:30 | Lorenzo Buffoni (University of Lisbon) | Deep Learning techniques for Genomics | Lecture |
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| 29 Aug, 2022 - 11:15-12:45 | Manuel Szewc (Jozef Stefan Institute, Ljubljana) | Interpretable graphical models for collider studies | Lecture |
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| 30 Aug, 2022 - 11:00-12:30 | Jesse Thaler (MIT) | Machine learning for HEP | Lecture |
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| 31 Aug, 2022 - 11:00-12:30 | Alessandra Cappati (LLR, Ecole Polytechnique, Paris) , Robert Schöfbeck (HEPHY Vienna) | Exploring EFT with ML at the LHC | Lecture |
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| 01 Sep, 2022 - 11:00-12:30 | Marat Freytsis (Rutgers University) | Recurrent NNs for fast signal discovery in pulsar timing arrays | Lecture |
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| 02 Sep, 2022 - 11:00-12:30 | Eliska Greplova (TU Delft) | Learning of Phases of Matter: What’s Next? | Lecture |
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| 12 Sep, 2022 - 11:00-11:15 | Welcome | Introduction |
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| 12 Sep, 2022 - 11:00-12:30 | David Shih | Introduction to normalizing flows and some applications to LHC and Gaia | Lecture |
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| 13 Sep, 2022 - 11:00-12:30 | Guido D'Amico | The Cosmological Analysis of Large-Scale-Structure Data | Lecture |
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| 14 Sep, 2022 - 11:00-12:30 | Jeff Byers (University of Padova) | Machine Learning and Physics: A Faustian Bargain? | Lecture |
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| 15 Sep, 2022 - 11:00-12:30 | Uros Seljak | Deterministic Langevin and Hamiltonian methods for sampling | Lecture |
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| 16 Sep, 2022 - 11:00-12:30 | Lorenzo Giambagli | Spectral Learning for Neural Network | Lecture |
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| 19 Sep, 2022 - 11:00-11:15 | Welcome | Introduction |
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| 19 Sep, 2022 - 11:15-12:45 | Lorenzo Chicchi | Spectral Learning | Lecture |
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| 20 Sep, 2022 - 11:00-12:30 | Giacomo Mazzamuto | Large-scale imaging and feature extraction using advanced high-resolution microscopy techniques | Lecture |
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| 21 Sep, 2022 - 11:00-12:30 | Nayara Fonseca, Veronica Guidetti | Generalization in Similarity Learning | Lecture |
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| 21 Sep, 2022 - 15:00-16:00 | Mara Salvato | ML applied to Identification/characterisation of X-ray sources and open problems | Talk |
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| 22 Sep, 2022 - 11:00-12:30 | Stefano Forte | PDF Determination as Machine Learning | Lecture |
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| 26 Sep, 2022 - 11:00-11:15 | Welcome | Introduction |
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| 27 Sep, 2022 - 11:00-12:30 | Mario Krenn | TBA | Lecture |
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| 28 Sep, 2022 - 11:00-12:30 | David Berman | On the Dynamics of Inference and Learning | Lecture |
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| 28 Sep, 2022 - 15:00-16:00 | Sebastiano Ariosto | Universal mean-field upper bound for the generalization gap of deep neural network | Lecture |
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| 29 Sep, 2022 - 11:00-12:30 | Benedetta Camaiani | Model independent measurements of Standard Model cross sections with Domain Adaptation | Lecture |
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| 29 Sep, 2022 - 15:00-16:00 | Paolo Nesi | TBA | Lecture |
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