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M. Vidal

4 papers hereh-index 581 citations18 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • math.ST2
  • math.PR1
  • stat.ME1
same name
  • M. Vidal — 60 papers, h 0
  • M. Vidal — 25 papers
  • M. Vidal — 17 papers, h 10
  • M. Vidal — 9 papers, h 35
  • M. Vidal — 9 papers, h 17
  • M. Vidal — 9 papers, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedBi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal

11 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

math.PR2026

An operator-theoretic characterization of Gaussian measure singularity under mean shifts

Marc Vidal

For two Gaussian random elements on a separable Hilbert space with common covariance operator, the fourth-order moment tensor structure of their mixture admits an operator-valued r…

math.ST2026

Noise-resilient penalty operators based on statistical differentiation schemes

Marc Vidal, Yves Rosseel

Classical approaches to penalized smoothing often rely on basis or kernel expansions, which constrain the estimator to a fixed span and may be restrictive for discretely observed d…

math.ST2024

Functional independent component analysis by choice of norm: a framework for near-perfect classification

Marc Vidal, Marc Leman, Ana M. Aguilera

We develop a theory for functional independent component analysis in an infinite-dimensional framework using Sobolev spaces that accommodate smoother functions. The notion of penal…

stat.ME2021★ 11 cited

Bi-Smoothed Functional Independent Component Analysis for EEG Artifact Removal

Marc Vidal, Mattia Rosso, Ana M. Aguilera

Motivated by mapping adverse artifactual events caused by body movements in electroencephalographic (EEG) signals, we present a functional independent component analysis based on t…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.