715 citations
- Istituto Nazionale di Fisica Nucleare, Sezione di TriesteIT79 papers
- Trieste Astronomical ObservatoryIT79 papers
- Institute for Fundamental Physics of the UniverseIT78 papers
- Scuola Internazionale Superiore di Studi AvanzatiIT78 papers
- Ludwig-Maximilians-Universität MünchenDE75 papers
- Max Planck Institute for AstronomyDE75 papers
- University of BolognaIT75 papers
- University of TriesteIT75 papers
- University of EdinburghGB74 papers
- Astronomical Observatory of CapodimonteIT73 papers
- Brera Astronomical ObservatoryIT73 papers
- California Institute of TechnologyUS73 papers
24 papers · 1 filter
Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions
A. Andrews, J. Jasche, G. Lavaux +147
A primary target of the \Euclid space mission is to constrain early-universe physics by searching for deviations from a primordial Gaussian random field. A significant detection of…
The GECo algorithm for Graph Neural Networks Explanation
Salvatore Calderaro, Domenico Amato, Giosuè Lo Bosco +2
Graph Neural Networks (GNNs) are powerful models that can manage complex data sources and their interconnection links. One of GNNs' main drawbacks is their lack of interpretability…
Generating the Traces You Need: A Conditional Generative Model for Process Mining Data
Riccardo Graziosi, Massimiliano Ronzani, Andrei Buliga +5
In recent years, trace generation has emerged as a significant challenge within the Process Mining community. Deep Learning (DL) models have demonstrated accuracy in reproducing th…
Euclid preparation: 6x2 pt analysis of Euclid's spectroscopic and photometric data sets
Euclid Collaboration, L. Paganin, M. Bonici +252
We present cosmological parameter forecasts for the Euclid 6x2pt statistics, which include the galaxy clustering and weak lensing main probes together with previously neglected cro…
Euclid preparation. L. Calibration of the linear halo bias in CDM cosmologies
Euclid Collaboration, T. Castro, A. Fumagalli +253
The Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric g…
Quantum enhanced stratification of Breast Cancer: exploring quantum expressivity for real omics data
Valeria Repetto, Elia Giuseppe Ceroni, Giuseppe Buonaiuto +1
Quantum Machine Learning (QML) is considered one of the most promising applications of Quantum Computing in the Noisy Intermediate Scale Quantum (NISQ) era for the impact it is tho…