Le Guen

Vincent Le Guen

Doctorant
Équipe : Données Complexes, Apprentissage et Représentations
Site web : https://www.linkedin.com/in/vincentleguen/
Bureau : 37.0E.36

Thèse "Deep learning pour la prévision spatio-temporelle -application à la prévision photovoltaïque" entre le CNAM (supervision: Nicolas Thome) et EDF R&D

2022

Articles de revue

  1. Le Guen, V. and Thome, N. Deep Time Series Forecasting with Shape and Temporal Criteria. In IEEE Transactions on Pattern Analysis and Machine Intelligence, 45 (1): 342-355, 2022. doi  www 

Articles de conférence

  1. Le Guen, V.; Rambour, C. and Thome, N. Complementing Brightness Constancy with Deep Networks for Optical Flow Prediction. In ECCV 2022, Springer, Tel Aviv, Israel, Lecture Notes in Computer Science, vol 13681 , 2022. doi  www 

2021

Articles de revue

  1. Yin, Y.; Le Guen, V.; Don`a, J.; de Bézenac, E.; Ayed, I.; Thome, N. and Gallinari, P. Augmenting physical models with deep networks for complex dynamics forecasting. In Journal of Statistical Mechanics: Theory and Experiment, 2021 (12): 124012, 2021. doi  www 

Articles de conférence

  1. Yin, Y.; Le Guen, V.; Dona, J.; Ayed, I.; de Bézenac, E.; Thome, N. and Gallinari, P. Augmenting physical models with deep networks for complex dynamics forecasting. In Ninth International Conference on Learning Representations ICLR 2021, Vienna (virtual), Austria, 2021. www 

Thèses et habilitations

  1. Le Guen, V. Deep learning for spatio-temporal forecasting - application to solar energy. Ph.D. Thesis, HESAM Université, 2021.

2020

Articles de conférence

  1. Le Guen, V. and Thome, N. Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity. In NeurIPS 2020, Vancouver, Canada, 2020. www 
  1. Le Guen, V. and Thome, N. A Deep Physical Model for Solar Irradiance Forecasting with Fisheye Images. In CVPR OmniCV worshop 2020, Seattle, United States, 2020. doi  www 
  1. Le Guen, V. and Thome, N. Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction. In Computer Vision and Pattern Recognition 2020 (CVPR), Seattle, United States, 2020. doi  www 

2019

Articles de revue

  1. Lajaunie, C.; Renard, D.; Quentin, A.; Le Guen, V. and Caffari, Y. A non-homogeneous model for kriging dosimetric data. In Mathematical Geosciences, 52 (7): 847-863, 2019. doi  www 

Articles de conférence

  1. Le Guen, V. and Thome, N. Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models. In Advances in Neural Information Processing Systems 32 (NeurIPS 2019), Vancouver, Canada, Advances in Neural Information Processing Systems 32 (NIPS 2019) proceedings 4191--4203, 2019. www 
  1. Le Guen, V. and Thome, N. Prévision de l'irradiance solaire par réseaux de neurones profonds `a l'aide de caméras au sol. In GRETSI 2019, Lille, France, 2019. www 

2018

Rapports

  1. Vasile, G.; Petrut, T.; Bellemain, P.; Ionescu, G.; Zozor, S.; de Oliveira, E.; d'Urso, G.; Hachet, G.; Le Guen, V.; Girard, A.; Philippe, O. and Hieramente, F. Synthèse des résultats du prototype V01 (1ère génération). Technical Report, GIPSA-LAB ; FEDER progress report, 2018.

2014

Articles de revue

  1. Le Guen, V. Cartoon+ texture image decomposition by the TV-L1 model. In Image Processing On Line, 4: 204-219, 2014. doi  www 
Haut