1 code implementation • 21 Mar 2024 • Nathan Mankovich, Homer Durand, Emiliano Diaz, Gherardo Varando, Gustau Camps-Valls
Detecting latent confounders from proxy variables is an essential problem in causal effect estimation.
no code implementations • 4 Mar 2024 • Homer Durand, Gherardo Varando, Nathan Mankovich, Gustau Camps-Valls
We introduce a causal regularisation extension to anchor regression (AR) for improved out-of-distribution (OOD) generalisation.
1 code implementation • 8 Jan 2024 • Nathan Mankovich, Gustau Camps-Valls, Tolga Birdal
In this work, we present a unifying formalism for PCA and its variants, and introduce a framework based on the flags of linear subspaces, ie a hierarchy of nested linear subspaces of increasing dimension, which not only allows for a common implementation but also yields novel variants, not explored previously.
1 code implementation • 14 Dec 2023 • David Aristoff, Jeremy Copperman, Nathan Mankovich, Alexander Davies
This article introduces an advanced Koopman mode decomposition (KMD) technique -- coined Featurized Koopman Mode Decomposition (FKMD) -- that uses time embedding and Mahalanobis scaling to enhance analysis and prediction of high dimensional dynamical systems.
1 code implementation • ICCV 2023 • Nathan Mankovich, Tolga Birdal
This paper presents a new, provably-convergent algorithm for computing the flag-mean and flag-median of a set of points on a flag manifold under the chordal metric.
1 code implementation • CVPR 2022 • Nathan Mankovich, Emily King, Chris Peterson, Michael Kirby
We provide evidence that the flag median is robust to outliers and can be used effectively in algorithms like Linde-Buzo-Grey (LBG) to produce improved clusterings on Grassmannians.