Julie Keisler

Julie Keisler

Starting research position, Arches Team (INRIA Paris)

Teaching

Master MIA

Practical Work: Introduction to Deep Learning, Faculté des Sciences d'Orsay - Université Paris Saclay, 2025

Tutorial 1: Introduction to Pytorch
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Tutorial 2: Hyperparameters and Architecture Optimization
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Tutorial 3: Convolutional Neural Networks (CNNs)
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Tutorial 4: Generative Models (GANs)
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Tutorial 5: Generative Models (Diffusion)
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Tutorial 6: Graph Neural Networks
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Tutorial 7: Recurrent Neural Networks (RNNs)
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Supervision

M2 Internships, EDF R&D, 2024

Roxane Goffinet, Global forecasting models for a large number of time series, March 2024 - October 2024, co-supervised with Bachir Hamrouche and Guillaume Lambert, EDF R&D
Alban Derepas, Future evolution of the wind resource and the interest of machine learning methods for statistical wind downscaling , May 2024 - November 2024, co-supervised with Boutheina Oueslati, Yannig Goude and Claire Monteleoni, EDF R&D and INRIA Paris
Keshav Das, Automated selection of adaptive additive models, application to load consumption forecasting, September 2024 - February 2025, co-supervised with Margaux Brégère and Amaury Durand, EDF R&D