Ronan Fablet
24
Documents
Publications
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End-to-End Kalman Filter in a High Dimensional Linear Embedding of the ObservationsSTUOD 2021 - Stochastic Transport in Upper Ocean Dynamics Annual Workshop, Sep 2021, Londres, United Kingdom. pp.211-221, ⟨10.1007/978-3-031-18988-3_13⟩
Communication dans un congrès
hal-03906953v1
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Assimilation-based Learning of Chaotic Dynamical Systems from Noisy and Partial DataICASSP 2020 : International Conference on Acoustics, Speech, and Signal Processing, May 2020, Barcelona, Spain. ⟨10.1109/ICASSP40776.2020.9054718⟩
Communication dans un congrès
hal-02436060v2
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Learning Chaotic and Stochastic Dynamics from Noisy and Partial Observation using Variational Deep LearningCI'2020 : 10th International Conference on Climate Informatics, Sep 2020, Oxford, United Kingdom
Communication dans un congrès
hal-02941313v1
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Learning Constrained Dynamical Embeddings for Geophysical DynamicsCI 2019 : 9th International Workshop on Climate Informatics, 2019, Paris, France
Communication dans un congrès
hal-02285700v1
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Learning stochastic representations of geophysical dynamicsICASSP 2019 : 44th International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. ⟨10.1109/ICASSP.2019.8682929⟩
Communication dans un congrès
hal-02005403v1
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Sea surface dynamics reconstruction using neural networks based kalman filterIGARSS 2019 - International Geoscience and remote Sensing Symposium, Jul 2019, Yokohama, Japan. pp.1-5, ⟨10.1109/IGARSS.2019.8898086⟩
Communication dans un congrès
hal-02285697v1
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Residual Integration Neural NetworkICASSP 2019 : IEEE International Conference on Acoustics, Speech and Signal Processing, May 2019, Brighton, United Kingdom. ⟨10.1109/ICASSP.2019.8683447⟩
Communication dans un congrès
hal-02005399v1
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Data assimilation schemes as a framework for learning dynamical model from partial and noisy observationsEGU 2019 : General Assembly 2019 of the European Geosciences Union, Apr 2019, Vienna, Austria
Communication dans un congrès
hal-02110359v1
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Learning ocean dynamical priors from noisy data using assimilation-derived neural netsIGARSS 2019 - International Geoscience and remote Sensing Symposium, Jul 2019, Yokohama, Japan. pp.1-3, ⟨10.1109/IGARSS.2019.8900345⟩
Communication dans un congrès
hal-02285693v1
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Data-driven and learning-based approaches for the spatiotemporal interpolation of SLA fields from current and future satellite-derived altimeter data"25 Years of Progress in Radar Altimetry" Symposium, 2018, Punta Delgada, Azores, Portugal
Communication dans un congrès
hal-01800511v1
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Bilinear residual Neural Network for the identification and forecasting of dynamical systemsEUSIPCO 2018 : European Signal Processing Conference, Sep 2018, Rome, Italy. pp.1-5, ⟨10.23919/EUSIPCO.2018.8553492⟩
Communication dans un congrès
hal-01686766v1
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Deep learning models for geophysical spatio-temporal fields reconstruction50èmes Journées de Statistique, Société Française de Statistique, May 2018, Palaiseau, France
Communication dans un congrès
hal-01883213v1
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Réseaux de neurones artificiels pour la prédiction et la reconstruction de dynamiques océanographiquesCFPT 2018 - Conférence Française de Photogrammétrie et de Télédétection, Jun 2018, Marne-la-Vallée, France. pp.1-3
Communication dans un congrès
hal-01883211v1
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Sea surface temperature prediction and reconstruction using patch-level neural network representationsIGARSS 2018 : IEEE International Geoscience and Remote Sensing Symposium, Jul 2018, Valence, Spain. pp.1-4, ⟨10.1109/IGARSS.2018.8519345⟩
Communication dans un congrès
hal-01883209v1
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Neural network models for spatio-temporal geophysical fields reconstruction : application to sea surface temperatureEGU2018: 20th EGU General Assembly, Apr 2018, Vienne, Austria. pp.17913-2
Communication dans un congrès
hal-01883214v1
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Neural embedding for closure modelsCI'2022: 11th International Conference on Climate Informatics, May 2022, Asheville (North carolina), United States
Poster de conférence
hal-04231187v1
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End-To-End Kalman Filter In A High Dimensional Linear Embedding Of The ObservationsCI'2022: 11th International Conference on Climate Informatics, May 2022, Asheville (North carolina), United States
Poster de conférence
hal-04231191v1
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Analysis of Sea Surface Temperature Variability Using Machine LearningChapron, B., Crisan, D., Holm, D., Mémin, E., Radomska, A. (eds) Stochastic Transport in Upper Ocean Dynamics II. STUOD 2022. Part of the Mathematics of Planet Earth book series (MPE,volume 11). Springer, Cham. Print ISBN 978-3-031-40093-3 Online ISBN 978-3-031-40094-0, https://doi.org/10.1007/978-3-031-40094-0_11. pp.247-260, pp.247-260, 2024, ⟨10.1007/978-3-031-40094-0_11⟩
Chapitre d'ouvrage
hal-04309728v1
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Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations2021
Pré-publication, Document de travail
hal-02931101v7
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