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Robust Neural Particle Identification Models
Aziz Temirkhanov, Artem Ryzhikov, Denis Derkach +3
The volume of data processed by the Large Hadron Collider experiments demands sophisticated selection rules typically based on machine learning algorithms. One of the shortcomings…
New UTfit Analysis of the Unitarity Triangle in the Cabibbo-Kobayashi-Maskawa scheme
UTfit Collaboration, Marcella Bona, Marco Ciuchini +14
Flavour mixing and CP violation as measured in weak decays and mixing of neutral mesons are a fundamental tool to test the Standard Model (SM) and to search for new physics. New an…
Stokes inversion techniques with neural networks: analysis of uncertainty in parameter estimation
Lukia Mistryukova, Andrey Plotnikov, Aleksandr Khizhik +3
Magnetic fields are responsible for a multitude of Solar phenomena, including such destructive events as solar flares and coronal mass ejections, with the number of such events ris…
Understanding of the properties of neural network approaches for transient light curve approximations
Mariia Demianenko, Konstantin Malanchev, Ekaterina Samorodova +4
Modern-day time-domain photometric surveys collect a lot of observations of various astronomical objects and the coming era of large-scale surveys will provide even more informatio…
Latent Neural Stochastic Differential Equations for Change Point Detection
Artem Ryzhikov, Mikhail Hushchyn, Denis Derkach
Automated analysis of complex systems based on multiple readouts remains a challenge. Change point detection algorithms are aimed to locating abrupt changes in the time series beha…
Supernova Light Curves Approximation based on Neural Network Models
Mariia Demianenko, Ekaterina Samorodova, Mikhail Sysak +4
Photometric data-driven classification of supernovae becomes a challenge due to the appearance of real-time processing of big data in astronomy. Recent studies have demonstrated th…