CC-Webcast IN2P3 / CNRS

Machine Learning workshop IN2P3-IRFU

Date de début :

26/09/2022 11:00

Date de fin :

26/09/2022 11:20

Lieu :

amphithéatre Pierre Gilles De Gennes - APC

Ville :

Paris

Producteur :

L'Institut national de physique nucléaire et de physique des particules

Durée :

0:21:11

Type :

video/mp4

Format :

mp4

Résolution :

1280x720

Introduction Machine learning

Introduction

Orateurs: Alexandre Boucaud (APC / IN2P3), David Rousseau (IJCLab, CNRS/IN2P3, Université Paris-Saclay), Valérie Gautard (CEA-Irfu)

Dernières vidéos

0:21:11

Introduction Machine learning

26/09/2022 - 11:00

1:06:22

Boosting event generation and inference with new machine learning methods

26/09/2022 - 11:40

0:14:34

Maximum-A-posteriori estimate with Deep generative NEtworks for Source Separation (MADNESS)

26/09/2022 - 14:00

0:20:43

Classification of astrophysical image time series using convolutional attention

26/09/2022 - 14:20

0:15:59

Convolutional neural networks demultiplexing in large Micromegas detectors for muography purposes

26/09/2022 - 14:40

0:16:39

Machine Learning Algorithms for the Gamma Conversion Reconstruction in the ClearMind Project

26/09/2022 - 15:00

0:14:14

M4CAST : an emerging national collaborative effort for IA applications to accelerators physics and technologies

26/09/2022 - 15:50

0:21:13

Echo State Networks for Dynamic Aperture prediction

26/09/2022 - 16:10

0:17:41

LinacNet: a new architecture for linear accelerator surrogate model

26/09/2022 - 16:30

0:28:32

Hackathon to fill in IN2P3 ML web site

26/09/2022 - 16:50

0:19:42

An EIM-based compression-extrapolation tool for efficient treatment of homogenized cross-section data

27/09/2022 - 09:00

0:17:37

Calibration and evaluation of an unsupervised machine learning algorithm for β+ imaging using an intracerebral micro probe

27/09/2022 - 09:20

0:16:07

Optimized Reconstruction of the Position of Interaction in High-Performances-Cameras

27/09/2022 - 10:00

0:57:17

Dealing with uncertainties in Machine Learning

27/09/2022 - 10:50

0:33:56

Scope of IN2P3 ML project

27/09/2022 - 11:40

0:20:16

AISSAI semestre IN2P3

27/09/2022 - 14:00

0:25:53

IN2P3 School of Statistics

27/09/2022 - 14:20

0:21:10

Enhanced GNN models for track reconstruction with ATLAS ITk

27/09/2022 - 14:40

0:18:23

Reconstruction of electromagnetic showers in calorimeters using Deep Learning

27/09/2022 - 15:00

0:16:38

Missing data reconstruction using ML techniques in the gaseous TPC PandaX-III experiment

27/09/2022 - 15:20

0:21:59

GNN for hadronic flow calibration in ATLAS

27/09/2022 - 16:10

0:19:42

Multiview Symbolic Regression

27/09/2022 - 16:30

0:17:11

Multi-objective optimization for the CMS High Granularity Calorimeter Level 1 trigger

27/09/2022 - 16:50

0:35:36

European Open Science Cloud : open science, open data

27/09/2022 - 17:10

0:23:53

Deep learning for slit-less Spectroscopic Redshift survey Simulator (DISPERS)

28/09/2022 - 09:00

0:20:50

Deep Learning Applied to Cherenkov Telescope Array Images

28/09/2022 - 09:20

0:18:55

Data/MC adaptation with adversarial training in KM3NeT

28/09/2022 - 09:40

0:21:08

The ELAsTiCC data challenge: preparing the Fink broker for LSST

28/09/2022 - 10:00

0:15:16

Neural Posterior Estimation with Differentiable Simulators

28/09/2022 - 10:50

0:14:27

Auto-tuning of the material mapping with the ACTS track reconstruction suite

28/09/2022 - 11:10

0:32:24

Round table on emerging topic

28/09/2022 - 11:30

0:21:07

B decays reconstruction at Belle II using graph neural networks

28/09/2022 - 14:00

0:25:20

A new method for the data driven estimation of background using GAN

28/09/2022 - 14:20

0:17:22

Gamma-ray spectrometry of fission fragments: ML analysis of multi-dimensional spectra

28/09/2022 - 14:40