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A Perspective on Gaussian Processes for Earth Observation

A Perspective on Gaussian Processes for Earth Observation

2 July 2020
Gustau Camps-Valls
Dino Sejdinovic
Jakob Runge
Markus Reichstein
    GP
ArXiv (abs)PDFHTML

Papers citing "A Perspective on Gaussian Processes for Earth Observation"

13 / 13 papers shown
ATM-Net: Anatomy-Aware Text-Guided Multi-Modal Fusion for Fine-Grained Lumbar Spine Segmentation
ATM-Net: Anatomy-Aware Text-Guided Multi-Modal Fusion for Fine-Grained Lumbar Spine Segmentation
Sheng Lian
Dengfeng Pan
Jianlong Cai
Guang-Yong Chen
Zhun Zhong
Shaozi Li
Shen Zhao
Shuo Li
345
4
0
04 Apr 2025
On the Generalization of Representation Uncertainty in Earth Observation
On the Generalization of Representation Uncertainty in Earth Observation
Spyros Kondylatos
Nikolaos Ioannis Bountos
Dimitrios Michail
Xiao Xiang Zhu
Gustau Camps-Valls
Ioannis Papoutsis
587
4
0
10 Mar 2025
Artificial intelligence to advance Earth observation: a perspective
Artificial intelligence to advance Earth observation: a perspectiveIEEE Geoscience and Remote Sensing Magazine (GRSM), 2023
D. Tuia
Konrad Schindler
Begüm Demir
Gustau Camps-Valls
Xiao Xiang Zhu
...
Mihai Datcu
Jorge-Arnulfo Quiané-Ruiz
Volker Markl
Bertrand Le Saux
Rochelle Schneider
382
33
0
15 May 2023
Analysis, Characterization, Prediction and Attribution of Extreme
  Atmospheric Events with Machine Learning: a Review
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review
S. Salcedo-Sanz
Jorge Pérez-Aracil
G. Ascenso
Javier Del Ser
D. Casillas-Pérez
...
D. Barriopedro
R. García-Herrera
Marcello Restelli
M. Giuliani
A. Castelletti
AI4Cl
366
16
0
03 Jun 2022
Inference over radiative transfer models using variational and
  expectation maximization methods
Inference over radiative transfer models using variational and expectation maximization methodsMachine-mediated learning (ML), 2021
D. Svendsen
Daniel Hernández-Lobato
Luca Martino
Valero Laparra
Á. Moreno-Martínez
Gustau Camps-Valls
216
6
0
07 Apr 2022
Leveraging Pre-Images to Discover Nonlinear Relationships in
  Multivariate Environments
Leveraging Pre-Images to Discover Nonlinear Relationships in Multivariate EnvironmentsEuropean Signal Processing Conference (EUSIPCO), 2021
Ali Vosoughi
A. Wismüller
CML
140
24
0
01 Jun 2021
Integrating Domain Knowledge in Data-driven Earth Observation with
  Process Convolutions
Integrating Domain Knowledge in Data-driven Earth Observation with Process ConvolutionsIEEE Transactions on Geoscience and Remote Sensing (TGRS), 2021
D. Svendsen
M. Piles
Jordi Munoz-Marí
D. Luengo
Luca Martino
Gustau Camps-Valls
237
19
0
16 Apr 2021
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model
  Inversion
Deep Gaussian Processes for Biogeophysical Parameter Retrieval and Model InversionIsprs Journal of Photogrammetry and Remote Sensing (ISPRS J. Photogramm. Remote Sens.), 2020
D. Svendsen
Pablo Morales-Álvarez
A. Ruescas
Rafael Molina
Gustau Camps-Valls
265
32
0
16 Apr 2021
Retrieval of aboveground crop nitrogen content with a hybrid machine
  learning method
Retrieval of aboveground crop nitrogen content with a hybrid machine learning method
K. Berger
J. Verrelst
J. Féret
T. Hank
Matthias Wocher
W. Mauser
Gustau Camps-Valls
127
177
0
07 Dec 2020
Fusing Optical and SAR time series for LAI gap filling with multioutput
  Gaussian processes
Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processesRemote Sensing of Environment (RSE), 2019
L. Pipia
Jordi Munoz-Marí
E. Amin
Santiago Belda
Gustau Camps-Valls
J. Verrelst
145
93
0
05 Dec 2020
Deep Importance Sampling based on Regression for Model Inversion and
  Emulation
Deep Importance Sampling based on Regression for Model Inversion and Emulation
F. Llorente
Luca Martino
D. Delgado
G. Camps-Valls
375
22
0
20 Oct 2020
Living in the Physics and Machine Learning Interplay for Earth
  Observation
Living in the Physics and Machine Learning Interplay for Earth Observation
Gustau Camps-Valls
D. Svendsen
Jordi Cortés-Andrés
Álvaro Moreno-Martínez
Adrián Pérez-Suay
J. Adsuara
I. Martín
M. Piles
Jordi Munoz-Marí
Luca Martino
PINNAI4CE
176
6
0
18 Oct 2020
Kernel Methods and their derivatives: Concept and perspectives for the
  Earth system sciences
Kernel Methods and their derivatives: Concept and perspectives for the Earth system sciencesPLoS ONE (PLOS ONE), 2020
J. E. Johnson
Valero Laparra
Adrián Pérez-Suay
Miguel D. Mahecha
Gustau Camps-Valls
224
27
0
29 Jul 2020
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