Search Results for author:
Found 10 papers, 7 papers with code
Linear optimal transport subspaces for point set classification
Our approach employs the Linear Optimal Transport (LOT) transform to obtain a linear embedding of set-structured data.
Data-driven Identification of Parametric Governing Equations of Dynamical Systems Using the Signed Cumulative Distribution Transform
This paper presents a novel data-driven approach to identify partial differential equation (PDE) parameters of a dynamical system.
The Radon Signed Cumulative Distribution Transform and its applications in classification of Signed Images
Here we describe a new image representation technique based on the mathematics of transport and optimal transport.
A sliced-Wasserstein distance-based approach for out-of-class-distribution detection
These methods often require extensive training data, are computationally expensive, and are vulnerable to out-of-distribution samples, e. g., adversarial attacks.
Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Analysis
Transport-based metrics and related embeddings (transforms) have recently been used to model signal classes where nonlinear structures or variations are present.
End-to-End Signal Classification in Signed Cumulative Distribution Transform Space
This paper presents a new end-to-end signal classification method using the signed cumulative distribution transform (SCDT).
Local Sliced-Wasserstein Feature Sets for Illumination-invariant Face Recognition
Face recognition is then performed using a nearest subspace in R-CDT domain of local gradient distributions.
Invariance encoding in sliced-Wasserstein space for image classification with limited training data
However, they are known to underperform when training data are limited and thus require data augmentation strategies that render the method computationally expensive and not always effective.
Nearest Subspace Search in The Signed Cumulative Distribution Transform Space for 1D Signal Classification
This paper presents a new method to classify 1D signals using the signed cumulative distribution transform (SCDT).
Radon cumulative distribution transform subspace modeling for image classification
We present a new supervised image classification method applicable to a broad class of image deformation models.
