203 citations · 2.2k across the 52 of their papers we have counts for
9 papers · 1 filter
Interpolation and Gap Filling of Landsat Reflectance Time Series
Alvaro Moreno-Martinez, Marco Maneta, Gustau Camps-Valls +4
Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particu…
Physics-Aware Gaussian Processes in Remote Sensing
Gustau Camps-Valls, Luca Martino, Daniel H. Svendsen +5
Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has ex…
Gradient-based Automatic Look-Up Table Generator for Atmospheric Radiative Transfer Models
Jorge Vicent, Luis Alonso, Luca Martino +3
Atmospheric correction of Earth Observation data is one of the most critical steps in the data processing chain of a satellite mission for successful remote sensing applications. A…
Living in the Physics and Machine Learning Interplay for Earth Observation
Gustau Camps-Valls, Daniel H. Svendsen, Jordi Cortés-Andrés +7
Most problems in Earth sciences aim to do inferences about the system, where accurate predictions are just a tiny part of the whole problem. Inferences mean understanding variables…
Deep Importance Sampling based on Regression for Model Inversion and Emulation
F. Llorente, L. Martino, D. Delgado +1
Understanding systems by forward and inverse modeling is a recurrent topic of research in many domains of science and engineering. In this context, Monte Carlo methods have been wi…
A Joint introduction to Gaussian Processes and Relevance Vector Machines with Connections to Kalman filtering and other Kernel Smoothers
Luca Martino, Jesse Read
The expressive power of Bayesian kernel-based methods has led them to become an important tool across many different facets of artificial intelligence, and useful to a plethora of…
Adaptive quadrature schemes for Bayesian inference via active learning
F. Llorente, L. Martino, V. Elvira +2
Numerical integration and emulation are fundamental topics across scientific fields. We propose novel adaptive quadrature schemes based on an active learning procedure. We consider…
Marginal likelihood computation for model selection and hypothesis testing: an extensive review
Fernando Llorente, Luca Martino, David Delgado +1
This is an up-to-date introduction to, and overview of, marginal likelihood computation for model selection and hypothesis testing. Computing normalizing constants of probability m…
Importance Gaussian Quadrature
Víctor Elvira, Luca Martino, Pau Closas
Importance sampling (IS) and numerical integration methods are usually employed for approximating moments of complicated target distributions. In its basic procedure, the IS method…