22 citations · 27 across the 12 of their papers we have counts for
12 papers
Flexible Spectral-Normalized Neural Gaussian Process for Dynamic Aperture Prediction
Yousra El-Bachir, Frederik Van der Veken, Davide di Croce +4
We address the challenge of scalable uncertainty quantification in large-scale scientific applications, where complex state-of-the-art machine learning methods are often computatio…
A Structural FHMM for Interpretable Disease Trajectories in T2DM
Alessandro Mari, Ekaterina Krymova, Guillaume Obozinski +3
In this work, we propose a structural variant of the Factorial Hidden Markov Model (FHMM) for the analysis of disease trajectories in patients with Type 2 diabetes mellitus (T2DM).…
A Latent ODE Approach to Spatiotemporal Modeling of Cine Cardiac MRI
David Brüggemann, Ekaterina Krymova, Firat Özdemir +6
Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models use only a few image-derived…
Optimizing Dynamic Aperture Studies with Active Learning
D. Di Croce, M. Giovannozzi, E. Krymova +5
Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's mo…
Data-driven modeling of beam loss in the LHC
Ekaterina Krymova, Guillaume Obozinski, Michael Schenk +2
In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the pa…
Trend estimation and short-term forecasting of COVID-19 cases and deaths worldwide
Ekaterina Krymova, Benjamín Béjar, Dorina Thanou +7
Since the beginning of the COVID-19 pandemic, many dashboards have emerged as useful tools to monitor the evolution of the pandemic, inform the public, and assist governments in de…