4 citations · 9 across the 8 of their papers we have counts for
8 papers
Linear optimal transport subspaces for point set classification
Mohammad Shifat E Rabbi, Naqib Sad Pathan, Shiying Li +3
Learning from point sets is an essential component in many computer vision and machine learning applications. Native, unordered, and permutation invariant set structure space is ch…
Data-driven Identification of Parametric Governing Equations of Dynamical Systems Using the Signed Cumulative Distribution Transform
Abu Hasnat Mohammad Rubaiyat, Duy H. Thai, Jonathan M. Nichols +6
This paper presents a novel data-driven approach to identify partial differential equation (PDE) parameters of a dynamical system. Specifically, we adopt a mathematical "transport"…
A sliced-Wasserstein distance-based approach for out-of-class-distribution detection
Mohammad Shifat E Rabbi, Abu Hasnat Mohammad Rubaiyat, Yan Zhuang +1
There exist growing interests in intelligent systems for numerous medical imaging, image processing, and computer vision applications, such as face recognition, medical diagnosis,…
Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Analysis
Shiying Li, Abu Hasnat Mohammad Rubaiyat, Gustavo K. Rohde
Transport-based metrics and related embeddings (transforms) have recently been used to model signal classes where nonlinear structures or variations are present. In this paper, we…
End-to-End Signal Classification in Signed Cumulative Distribution Transform Space
Abu Hasnat Mohammad Rubaiyat, Shiying Li, Xuwang Yin +3
This paper presents a new end-to-end signal classification method using the signed cumulative distribution transform (SCDT). We adopt a transport-based generative model to define t…
Local Sliced-Wasserstein Feature Sets for Illumination-invariant Face Recognition
Yan Zhuang, Shiying Li, Mohammad Shifat-E-Rabbi +3
We present a new method for face recognition from digital images acquired under varying illumination conditions. The method is based on mathematical modeling of local gradient dist…
Invariance encoding in sliced-Wasserstein space for image classification with limited training data
Mohammad Shifat E Rabbi, Yan Zhuang, Shiying Li +3
Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform whe…
Learning Energy-Based Models With Adversarial Training
Xuwang Yin, Shiying Li, Gustavo K. Rohde
We study a new approach to learning energy-based models (EBMs) based on adversarial training (AT). We show that (binary) AT learns a special kind of energy function that models the…