AI is everywhere and suddenly everybody is an expert on machine learning. In this talk, I will try to give a gentle introduction the main topics in the design of machine learning algorithms and what guarantees we have they will work. The relationship between ML and empirical science method will be highlighted and some applications to the Physics domain discussed.
In this talk we will review some recent uses of machine learning techniques to perform calculations in strong gravity. These will include physics-informed neural networks (PINNs) for the solution of differential equations, and generative models such as GANs.
The Gaia mission as well as large-scale ground-based spectroscopic surveys are collecting complex data for millions (even billions) of stars. Within the Gaia group we are therefore been using more and more machine-learning methods to cope with the amount of data. In this talk I will present some examples from recent publications in which we have successfully used supervised (typically...
Neural Quantum States are at the basis of a new ab-initio method especially designed to tackle the quantum many-body problem. These combine the variational method with neural networks, a flagship tool of modern Machine Learning. Neural Quantum States have been successfully used in spin, electronic and nuclear many-body systems. Neural networks can provide an unbiased approximation of complex...
Machine learning techniques have a variety of use cases within the LHCb experiment. They are an essential ingredient to achieve the ultimate performance in event reconstruction and high precision in physics output. This talk will give an insight to the use of ML algorithms in online event selections performed by the LHCb trigger system, offline data analyses of physics measurements , as well...
Time-domain surveys are designed to study astrophysical transient phenomena appearing in the night sky. The improvements in instrumentation and data analysis are allowing the new generation of surveys to discover several thousand (and soon to be millions) of events per night. However, some of such discoveries are associated with spurious detections related to spikes from bright stars,...
The growing significance of Gravitational Wave Astrophysics puts in evidence the need of techniques capable of effectively and reliably analyzing all the collected data. Furthermore, the search for lensing signatures within gravitational-wave signals is a challenging task that holds the potential to uncover fresh insights into fundamental physics, astrophysics, and cosmology. In this context,...
