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Malvasia – MAchine Learning to VAlue Single Interferometer Analysis

Malvasia – MAchine Learning to VAlue Single Interferometer Analysis

Oct 10, 2024 | 2021, diiP, Masters Internship, Physics/Astronomy

2021Masters Projects@Physics and Astronomy +Computer Science+Mathematics/Statistics+Physics/Astronomy #gravitational wave#deep learning  Project SummaryThe direct observation of gravitational waves (GW) by the LIGO and Virgo detectors is one of the breakthrough...
Artificial Intelligence for source deblending in the next generation of astrophysical big data imaging surveys – Combining Euclid and LSST

Artificial Intelligence for source deblending in the next generation of astrophysical big data imaging surveys – Combining Euclid and LSST

Oct 10, 2024 | 2021, diiP, Masters Internship, Physics/Astronomy

2021Masters Projects@Physics and Astronomy +Computer Science+Mathematics/Statistics+Physics/Astronomy #cosmology#astrophysics#probabilistic deep learning#image processing  Project SummaryAstronomy, as many other disciplines, is entering a big data era. The next...
Compact representations to detect gravitational waves from extreme-mass ratio inspirals

Compact representations to detect gravitational waves from extreme-mass ratio inspirals

Oct 10, 2024 | 2024, diiP, Masters Internship, Physics/Astronomy

2024 Master’s Projects@Physics/Astronomy #Gravitational waves#extreme-mass ratio inspirals#data representations#neural networks  Project Summary Extreme Mass Ratio Inspirals (EMRIs), detectable only by the future space-based detector LISA, provide a unique...
Investigating Diffusion Models for Astronomical Image Deconvolution – boosting the synergy between Euclid and LSST

Investigating Diffusion Models for Astronomical Image Deconvolution – boosting the synergy between Euclid and LSST

Oct 10, 2024 | 2024, diiP, Masters Internship, Physics/Astronomy

2024 Master’s Projects@Physics/Astronomy #diffusion models #image processing #deconvolution   🎉This project has been accepted at the ML4Physics workshop at NeurIPS! Project Summary This project tackles the problem of deconvolving astronomical images to...
Accelerate Discoveries (boosting) Astroparticle Physics (analysis) Techniques – ADAPT

Accelerate Discoveries (boosting) Astroparticle Physics (analysis) Techniques – ADAPT

Oct 10, 2024 | 2024, diiP, Physics/Astronomy, Strategic projects

2024 Strategic Projects @Physics/Astronomy #Self-supervised Learning#Semi-supervised Learning#Sensitivity enhancement#Data Analysis based on AI Project Summary The aim of the ADAPT project was to develop a novel analysis strategy for the KM3NeT astroparticle physics...
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  • Nikos Paragios – Seeing the Invisible – Doing the Impossible: Reinventing Healthcare with Generative AI-powered diagnosis, treatment and beyond
  • Deeply Learning from Neutrino Interactions with the KM3NeT neutrino telescope
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