Все публикации

1:03:42

Star clusters near and far: mapping galaxy evolution through parsec scales physical processes

1:29:51

« LA VIE AILLEURS ? »

1:38:26

« L'ÉCOLE (PUBLIQUE ET PRIVÉE) ET LA RÉPUBLIQUE »

1:27:11

« D'AUTRES MONDES DANS LE COSMOS ? »

1:05:10

Cosmic ray feedback and magnetic dynamos in galaxy formation

1:17:40

« LES ÉTOILES PRIMITIVES, TRACES FOSSILES DES ORIGINES DE NOTRE VOIE LACTÉE »

1:03:36

Dark matter searches: status and prospects

0:00:59

L’Institut d’astrophysique de Paris vous souhaite une excellente année 2024 !

1:00:46

Review: Deep learning algorithms for morphological classification of galaxies (H. Dominguez-Sanchez)

0:16:00

Generative Topographic Mapping for tomographic redshift estimates

0:15:18

Anomaly detection using local measures of uncertainty in latent representations

0:03:18

Assessing and Benchmarking the Fidelity of Posterior Inference Methods for Astrophysics Data An ...

0:15:23

HySBI - Hybrid Simulation-Based Inference

0:03:38

CNNs reveal crucial degeneracies in strong lensing subhalo detection

0:13:29

Extending the Reach of Gaia DR3 with Self-Supervision

0:11:21

Efficient and fast deep learning approaches to denoise large radioastronomy line cubes ​and to ...

1:28:54

ML-IAP/CCA-2023: Debate #2 'What can machine-learning do for the next generation surveys?'

0:13:45

Who threw that rock? Tracing the path of martian meteorites back to the crater of origin using ML

0:12:12

Explaining dark matter halo abundance with interpretable deep learning

0:14:05

Doing More With Less; Label-Efficient Learning for Euclid and Rubin

1:23:40

ML-IAP/CCA-2023: Debate #1 'Is there truth in latent space?'

0:03:30

Extracting physical rules from ensemble machine learning for the selection of radio AGN.

0:03:24

Fishnets: Mapping Information Geometry with Robust, Scalable Neural Compression

0:13:17

The terms Eisenstein and Hu missed