4 papers
Disentangling Forced and Internal Climate Variability in Single Realizations using Dynamic Mode Decomposition with Control
Nathan Mankovich, Andrei Gavrilov, Gustau Camps-Valls
We show that a single climate realization can be decomposed into forced and internal components by treating external forcing as a dynamical driver within a linear stochastic system…
Feature Extraction in the Remote Sensing Data Value Chain: A Systematic Review of Methods and Applications
Nathan Mankovich, Kai-Hendrik Cohrs, Homer Durand +3
Earth observation involves collecting, analyzing, and processing an ever-growing mass of data. This planetary data is crucial for addressing relevant societal, economic, and enviro…
A Flag Decomposition for Hierarchical Datasets
Nathan Mankovich, Ignacio Santamaria, Gustau Camps-Valls +1
Flag manifolds encode nested sequences of subspaces and serve as powerful structures for various computer vision and machine learning applications. Despite their utility in tasks s…
Out-of-distribution robustness for multivariate analysis via causal regularisation
Homer Durand, Gherardo Varando, Nathan Mankovich +1
We propose a regularisation strategy of classical machine learning algorithms rooted in causality that ensures robustness against distribution shifts. Building upon the anchor regr…