J. Emmanuel Johnson
J. Emmanuel Johnson
Postdoctoral Researcher
Verified email at - Homepage
Cited by
Cited by
Wind-driven circulation in a shallow microtidal estuary: The Indian River Lagoon
RJ Weaver, JE Johnson, M Ridler
Journal of Coastal Research 32 (6), 1333-1343, 2016
Estimation of oceanic particulate organic carbon with machine learning
R Sauzède, JE Johnson, H Claustre, G Camps-Valls, AB Ruescas
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information …, 2020
Accounting for input noise in Gaussian process parameter retrieval
JE Johnson, V Laparra, G Camps-Valls
IEEE Geoscience and Remote Sensing Letters 17 (3), 391 - 395, 2019
Kernel methods and their derivatives: Concept and perspectives for the earth system sciences
JE Johnson, V Laparra, A Pérez-Suay, MD Mahecha, G Camps-Valls
Plos one 15 (10), e0235885, 2020
Information theory in density destructors
JE Johnson, V Laparra, R Santos-Rodriguez, G Camps-Valls, J Malo
arxiv, 2019
Information theory measures via multidimensional gaussianization
V Laparra, JE Johnson, G Camps-Valls, R Santos-Rodríguez, J Malo
arXiv preprint arXiv:2010.03807, 2020
Rotnet: Fast and scalable estimation of stellar rotation periods using convolutional neural networks
JE Johnson, S Sundaresan, T Daylan, L Gavilan, DK Giles, SI Silva, ...
arXiv preprint arXiv:2012.01985, 2020
Gaussianizing the Earth: Multidimensional Information Measures for Earth Data Analysis
JE Johnson, V Laparra, M Piles, G Camps-Valls
IEEE Geoscience and Remote Sensing Magazine, 2021
Schroedinger Eigenmaps for manifold alignment of multimodal hyperspectral images
JE Johnson
Rochester Institute of Technology, 2016
Manifold alignment with Schroedinger eigenmaps
JE Johnson, CM Bachmann, ND Cahill
Algorithms and Technologies for Multispectral, Hyperspectral, and …, 2016
Orthonormal convolutions for the rotation based iterative gaussianization
V Laparra, A Hepburn, JE Johnson, J Malo
2022 IEEE International Conference on Image Processing (ICIP), 4018-4022, 2022
The Kernelized Taylor Diagram
K Wickstrøm, JE Johnson, S Løkse, G Camps-Valls, KØ Mikalsen, ...
Symposium of the Norwegian AI Society, 125-131, 2022
Estimating information in Earth data cubes
JE Johnson, E Diaz, V Laparra, M Mahecha, D Miralles, G Camps-Valls
EGU General Assembly Conference Abstracts, 12702, 2018
Learning latent functions for causal discovery
E Díaz, G Varando, JE Johnson, G Camps-Valls
Machine Learning: Science and Technology, 2023
Learning relevant features of optical water types
K Blix, AB Ruescas, JE Johnson, G Camps-Valls
IEEE Geoscience and Remote Sensing Letters 19, 1-5, 2021
Disentangling derivatives, uncertainty and error in gaussian process models
JE Johnson, V Laparra, G Camps-Valls
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018
Invertible neural networks for satellite retrievals of aerosol optical depth
P Pelucchi, J Vicent, JE Johnson, P Stier, G Camps-Valls
EGU23, 2023
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
JE Johnson, R Lguensat, R Fablet, E Cosme, JL Sommer
arXiv preprint arXiv:2211.10444, 2022
Clouds aware flood extent segmentation for emergency response services
G Mateo-Garcia, E Portales, F Liu, E Nemni, JE Johnson, L Kruitwagen, ...
AGU Fall Meeting Abstracts 2021, NH44A-05, 2021
Spatio-Temporal Gaussianization Flows for Extreme Event Detection
MÁ Fernández-Torres, JE Johnson, M Piles, G Camps-Valls
EGU General Assembly Conference Abstracts, EGU21-15729, 2021
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