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20112023
most citedHyperspectral Super-Resolution with Coupled Tucker Approximation: Recoverability and SVD-based algorithms

92 citations · 312 across the 12 of their papers we have counts for

collaborators

12 papers

math.NA2023

On factorization of rank-one auto-correlation matrix polynomials

Konstantin Usevich, Julien Flamant, Marianne Clausel +1

This article characterizes the rank-one factorization of auto-correlation matrix polynomials. We establish a sufficient and necessary uniqueness condition for uniqueness of the fac…

eess.SP2022★ 4 cited

Coupled CP tensor decomposition with shared and distinct components for multi-task fMRI data fusion

Ricardo Augusto Borsoi, Isabell Lehmann, Mohammad Abu Baker Siddique Akhonda +4

Discovering components that are shared in multiple datasets, next to dataset-specific features, has great potential for studying the relationships between different subjects or tas…

eess.SP2022

Polarimetric phase retrieval: uniqueness and algorithms

Julien Flamant, Konstantin Usevich, Marianne Clausel +1

This work introduces a novel Fourier phase retrieval model, called polarimetric phase retrieval that enables a systematic use of polarization information in Fourier phase retrieval…

cs.LG2021

Tensor-based framework for training flexible neural networks

Yassine Zniyed, Konstantin Usevich, Sebastian Miron +1

Activation functions (AFs) are an important part of the design of neural networks (NNs), and their choice plays a predominant role in the performance of a NN. In this work, we are…

math.OC2021★ 31 cited

A general framework for constrained convex quaternion optimization

Julien Flamant, Sebastian Miron, David Brie

This paper introduces a general framework for solving constrained convex quaternion optimization problems in the quaternion domain. To soundly derive these new results, the propose…

eess.SP2020★ 64 cited

Coupled Tensor Decomposition for Hyperspectral and Multispectral Image Fusion with Inter-Image Variability

Ricardo Augusto Borsoi, Clémence Prévost, Konstantin Usevich +3

Coupled tensor approximation has recently emerged as a promising approach for the fusion of hyperspectral and multispectral images, reconciling state of the art performance with st…