Fisher-Rao and pullback Hilbert cone distances on the multivariate Gaussian manifold with applications to simplification and quantization of mixtures
F Nielsen - Topological, Algebraic and Geometric Learning …, 2023 - proceedings.mlr.press
Data sets of multivariate normal distributions abound in many scientific areas like diffusion
tensor medical imaging, structure tensor computer vision, radar signal processing, machine …
tensor medical imaging, structure tensor computer vision, radar signal processing, machine …
Multidimensional complex stationary centered Gaussian autoregressive time series machine learning in Poincaré and Siegel disks: application for audio and radar …
Y Cabanes - 2022 - theses.hal.science
The objective of this thesis is the classification of complex valued stationary centered
Gaussian autoregressive time series. We study the case of one-dimensional time series as …
Gaussian autoregressive time series. We study the case of one-dimensional time series as …
Leveraging Optimal Transport via Projections on Subspaces for Machine Learning Applications
C Bonet - arXiv preprint arXiv:2311.13883, 2023 - arxiv.org
Optimal Transport has received much attention in Machine Learning as it allows to compare
probability distributions by exploiting the geometry of the underlying space. However, in its …
probability distributions by exploiting the geometry of the underlying space. However, in its …
Fisher-Rao distance and pullback SPD cone distances between multivariate normal distributions
F Nielsen - arXiv preprint arXiv:2307.10644, 2023 - arxiv.org
Data sets of multivariate normal distributions abound in many scientific areas like diffusion
tensor imaging, structure tensor computer vision, radar signal processing, machine learning …
tensor imaging, structure tensor computer vision, radar signal processing, machine learning …
[PDF][PDF] Overview of some contributions on computational geometry on various geometric structures beyond the Euclidean structure
F Nielsen - franknielsen.github.io
Let M={pθ (x), θ∈ Θ} be a parametric statistical model (regular or not). Examples of regular
statistical models are the families of categorical and Gaussian distributions (exponential …
statistical models are the families of categorical and Gaussian distributions (exponential …
[PDF][PDF] List of selected peer-reviewed publications
F Nielsen - franknielsen.github.io
[63] Junlin Yao and Frank Nielsen.“SSSC-AM: A unified framework for video co-
segmentation by structured sparse subspace clustering with appearance and motion …
segmentation by structured sparse subspace clustering with appearance and motion …
[PDF][PDF] Multidimensional stationary time series Machine Learning for Radar Clutter Classification
We present a method to classify complex valued stationary centered Gaussian
autoregressive time series. Our initial motivation comes from radar signal processing and …
autoregressive time series. Our initial motivation comes from radar signal processing and …