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Deep inference of seabird dives from GPS-only records: Performance and generalization properties

PLoS computational biology, 2022-03, Vol.18 (3), p.e1009890-e1009890

2022

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CNN-Based Target Recognition and Identification for Infrared Imaging in Defense Systems

Sensors (Basel, Switzerland), 2019-04, Vol.19 (9), p.2040

2019

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Residual Networks as Flows of Diffeomorphisms

Journal of mathematical imaging and vision, 2020-04, Vol.62 (3), p.365-375

2020

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A Transformer Network With Sparse Augmented Data Representation and Cross Entropy Loss for AIS-Based Vessel Trajectory Prediction

IEEE access, 2024, Vol.12, p.21596-21609

2024

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A Deep Learning Approach to Extract Balanced Motions From Sea Surface Height Snapshot

Geophysical research letters, 2024-04, Vol.51 (7), p.n/a

2024

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Hidden Markov models: the best models for forager movements?

PloS one, 2013-08, Vol.8 (8), p.e71246-e71246

2013

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Brain MRI super-resolution using deep 3D convolutional networks

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017, p.197-200

2017

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A Posteriori Learning for Quasi‐Geostrophic Turbulence Parametrization

Journal of advances in modeling earth systems, 2022-11, Vol.14 (11), p.1-n/a

2022

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Contrasted Trends in Chlorophyll‐a Satellite Products

Geophysical research letters, 2024-07, Vol.51 (14), p.1-n/a

2024

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Broad impacts of fine-scale dynamics on seascape structure from zooplankton to seabirds

Nature communications, 2014-10, Vol.5 (1), p.5239-5239, Article 5239

2014

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Intercomparison of Data-Driven and Learning-Based Interpolations of Along-Track Nadir and Wide-Swath SWOT Altimetry Observations

Remote sensing (Basel, Switzerland), 2020-11, Vol.12 (22), p.3806

2020

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Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review

IEEE/CAA journal of automatica sinica, 2023-06, Vol.10 (6), p.1361-1387

2023

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End-to-End Neural Interpolation of Satellite-Derived Sea Surface Suspended Sediment Concentrations

Remote sensing (Basel, Switzerland), 2022-08, Vol.14 (16), p.4024-16

2022

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Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

Remote sensing (Basel, Switzerland), 2018-12, Vol.10 (12), p.1864

2018

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Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning

Remote sensing (Basel, Switzerland), 2022-02, Vol.14 (4), p.851

2022

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Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks

IEEE journal of selected topics in applied earth observations and remote sensing, 2023, Vol.16, p.1-13

2023

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Editorial: AI and remote sensing in ocean sciences

Frontiers in Marine Science, 2024-01, Vol.10

2024

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Ensemble-based 4DVarNet uncertainty quantification for the reconstruction of sea surface height dynamics

Environmental Data Science, 2023, Vol.2, Article e18

2023

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Unsupervised Reconstruction of Sea Surface Currents from AIS Maritime Traffic Data Using Trainable Variational Models

Remote sensing (Basel, Switzerland), 2021-08, Vol.13 (16), p.3162

2021

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Ensemble-based 4DVarNet uncertainty quantification for the reconstruction of sea surface height dynamics – ERRATUM

Environmental Data Science, 2023, Vol.2, Article e33

2023

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Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields

Frontiers in applied mathematics and statistics, 2021-05, Vol.7

2021

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A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers

Frontiers in Marine Science, 2023-03, Vol.10, p.1-20

2023

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Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework

Machine learning: science and technology, 2023-06, Vol.4 (2), p.25018

2023

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Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 2020, 12, 4156

Remote sensing (Basel, Switzerland), 2022-11, Vol.14 (22), p.5669

2022

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Data-Driven Interpolation of Sea Surface Suspended Concentrations Derived from Ocean Colour Remote Sensing Data

Remote sensing (Basel, Switzerland), 2021-09, Vol.13 (17), p.3537

2021

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Deep inference of seabird dives from GPS-only records: Performance and generalization properties

CNN-Based Target Recognition and Identification for Infrared Imaging in Defense Systems

Residual Networks as Flows of Diffeomorphisms

A Transformer Network With Sparse Augmented Data Representation and Cross Entropy Loss for AIS-Based Vessel Trajectory Prediction

A Deep Learning Approach to Extract Balanced Motions From Sea Surface Height Snapshot

Hidden Markov models: the best models for forager movements?

Brain MRI super-resolution using deep 3D convolutional networks

A Posteriori Learning for Quasi‐Geostrophic Turbulence Parametrization

Contrasted Trends in Chlorophyll‐a Satellite Products

Broad impacts of fine-scale dynamics on seascape structure from zooplankton to seabirds

Intercomparison of Data-Driven and Learning-Based Interpolations of Along-Track Nadir and Wide-Swath SWOT Altimetry Observations

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review

End-to-End Neural Interpolation of Satellite-Derived Sea Surface Suspended Sediment Concentrations

Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

Semantic Segmentation of Metoceanic Processes Using SAR Observations and Deep Learning

Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks

Editorial: AI and remote sensing in ocean sciences

Ensemble-based 4DVarNet uncertainty quantification for the reconstruction of sea surface height dynamics

Unsupervised Reconstruction of Sea Surface Currents from AIS Maritime Traffic Data Using Trainable Variational Models

Ensemble-based 4DVarNet uncertainty quantification for the reconstruction of sea surface height dynamics – ERRATUM

Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields

A Multi-Mode Convolutional Neural Network to reconstruct satellite-derived chlorophyll-a time series in the global ocean from physical drivers

Extending the extended dynamic mode decomposition with latent observables: the latent EDMD framework

Correction: Martinez et al. Neural Network Approaches to Reconstruct Phytoplankton Time-Series in the Global Ocean. Remote Sens. 2020, 12, 4156

Data-Driven Interpolation of Sea Surface Suspended Concentrations Derived from Ocean Colour Remote Sensing Data

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