Deep CosmoStat Days

Liste des Contributions

18. Introduction

Jean-Luc Starck (CosmoStat, CEA Paris-Saclay)

12/02/2026 09:40

5. Modelling Uncertainty in Multi-Source Data Fusion

Grigorios Tsagkatakis (FORTH)

12/02/2026 09:50

14. On Diffusion Models for Inverse Problems

François LANUSSE (AIM, CNRS/CEA Paris-Saclay)

12/02/2026 10:20

Diffusion models are emerging as powerful tools for probabilistic prediction and inference in the physical sciences, but their application faces key challenges: high-dimensional state spaces, partial observability, and expensive simulations. In this talk, I present a unified diffusion-based framework addressing these issues across three complementary directions. First, latent-space diffusion...

17. CHEM- Estimating and Understanding Hallucinations in Deep Learning for Image Processing

Ines Rosellon Inclan (LMU)

12/02/2026 10:50

U-Net and other U-shaped architectures have become standard tools for image deconvolution in astronomy and related imaging tasks. Despite their success, these models might produce unrealistic artifacts, or hallucinations, which can compromise analysis in safety-critical settings. In this talk, I will present CHEM (Conformal Hallucination Estimation Metric), a general framework for identifying...

7. Learnlets on the sphere

Victor Bonjean (FORTH)

12/02/2026 11:10

1. A plug-and-play approach with fast uncertainty quantification for weak lensing mass mapping

Hubert Leterme (CEA IRFU/DAp)

12/02/2026 11:30

Stage-IV surveys such as Euclid will deliver vast amounts of high-precision data, opening new opportunities to constrain cosmological models with unprecedented accuracy. A key step in this process is the reconstruction of the dark matter distribution from noisy weak lensing shear measurements. Current deep learning-based mass mapping methods achieve high accuracy, but either require retraining...

16. The Hubble Tension in Light of the Symmetry of Scale Invariance

Prof. Frederic Courbin (ICCUB - IEEC - ICREA)

12/02/2026 14:25

When the expansion rate of the Universe at recombination is used to infer the present expansion rate 𝐻0, the value derived in the ΛCDM model, 𝐻0 =67.4 km s−1 Mpc−1, is about in 6 𝜎 tension with the value measured locally, 𝐻0 =74 km s−1 Mpc−1. In this work, we consider instead the expansion history in the context of the symmetry of scale-invariant vacuum (SIV model). We first perform two major...

3. UNIONS cosmological results with 2D weak lensing

Martin KILBINGER (CEA Saclay/Irfu/DAp)

12/02/2026 14:55

Weak lensing

2. Inferring 3D shapes and measuring intrinsic alignments of galaxies with UNIONS

Antonin Corinaldi (CEA Paris-Saclay / AIM / CosmoStat)

12/02/2026 15:25

Weak lensing

Galaxies are subject to intrinsic alignments, which correspond to the correlations between their 3D shapes and orientations and the underlying tidal field of dark matter across the large-scale structure of the Universe. This intrinsic galaxy alignment is traditionally measured with the two-point galaxy-density correlation function projected in the sky plane. However, the projection of 3D...

4. Impact of Baryonic Physics on Weak Lensing Statistics

Andreas Tersenov

12/02/2026 16:10

Weak lensing

Weak gravitational lensing is a powerful probe of cosmology, but its small-scale information is affected by baryonic feedback from galaxy formation processes. Higher-order statistics offer access to non-Gaussian information beyond the angular power spectrum, yet their sensitivity to baryonic effects remains an open question. In this work, we study the impact of baryonic physics on cosmological...

11. Probing large-scale structures through cross-correlations of the tSZ effect

Emma Aycoberry (CosmoStat, CEA Paris-Saclay)

12/02/2026 16:30

Weak lensing

Cross-correlations between the thermal Sunyaev–Zel’dovich (tSZ) effect and tracers of large-scale structure provide a powerful probe of both astrophysics and cosmology. In this talk, I will present results on the cross-correlation of the tSZ signal with weak gravitational lensing and galaxy clustering in the context of the Euclid mission. These measurements allow us to study the distribution...

19. Convergence map emulator & validation

Vilasini Tinnaneri Sreekanth

12/02/2026 16:50

Weak lensing

20. AI Vision for the battlefield: IMINT and Embedded Video Processing

Dr Arnaud Woiselle (Safran)

12/02/2026 17:10

13. Learning Domain-Invariant Representations via Optimal Transport and Spectral Embeddings

Dr Fred Ngole (CEA/DRT)

13/02/2026 10:00

IA

In many learning problems, labeled data are available only in a source domain, while the target domain remains unlabeled and distributionally different. This talk introduces a principled approach to unsupervised domain adaptation based on optimal transport. By interpreting transport plans between source and target distributions as weighted graphs and embedding them spectrally, the method...

9. Inferring Physical Properties of High-z Galaxies from IFU Spectral Data cubes: Signal Enhancement and Data-Driven Mapping Beyond Power-Law Relations

Arnab Lahiry (FORTH)

13/02/2026 10:30

IA

Studies of galaxy evolution at z≳3 are limited by low signal-to-noise ratios and the difficulty of extracting faint, spatially resolved signals. I briefly summarise my first PhD project on denoising and signal restoration of high-redshift IFU datacubes, including the development of a dedicated software framework for generating and analysing controlled toy-model simulations. Wavelet-based...

10. Uncertainty Quantification for Generative Models in Astrophysics

Sammy Sharief (CEA)

13/02/2026 10:50

IA

As astronomy enters a new era of big data, machine learning, and novel generative models enable inference in high-dimensional spaces and help tackle previously intractable problems. In this context, defining and measuring the accuracy of inferred posteriors, especially in high-dimensional parameter spaces such as images, has become increasingly pressing. Specifically, two questions need to be...

6. Foreground removal in HI 21 cm intensity mapping under frequency-dependent beam distortions

Athanasia Gkogkou (IA/ICS-FORTH)

13/02/2026 11:30

Radio Astronomy

Neutral hydrogen (HI) intensity mapping with single-dish telescopes is a powerful probe of post-reionization cosmology, but extracting the signal is challenging due to bright foregrounds and realistic, frequency-dependent beam effects that degrade most standard methods. I present an evaluation of SDecGMCA, a spherical extension of GMCA that combines sparse component separation with explicit...

12. Generative model for shear inference in the context of radio weak gravitational lensing

Ezequiel Centofanti (CosmoStat, CEA Paris-Saclay)

13/02/2026 11:50

Radio Astronomy

Next-generation radio interferometers, such as the SKA, will observe the radio sky with unprecedented sensitivity and resolution. Their wide sky coverage will also enable weak lensing studies using radio data. Radio weak lensing not only complements optical observations, but also allows access to higher redshifts. However, traditional shear estimation methods—based on measuring the ellipticity...

8. Starlet l1-norm for neutral hydrogen intensity mapping

Pauline Gorbatchev (FORTH)

13/02/2026 12:10

Radio Astronomy

Neutral hydrogen intensity mapping encodes valuable non-Gaussian cosmological information, particularly at late times in the Universe’s evolution. Traditional two-point statistics, such as the angular power spectrum, are not sensitive to this information. In this work, we employ the starlet l1-norm, a multi-scale, higher-order statistic robust to instrumental effects to capture non-Gaussian...

Retour à l'événement