On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid [PDF]
Entropy, 2020 The Jensen−Shannon divergence is a renown bounded symmetrization of the Kullback−Leibler divergence which does not require probability densities to have matching supports. In this paper, we introduce a vector-skew generalization of the scalar
Frank Nielsen
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Tight Bounds Between the Jensen–Shannon Divergence and the Minmax Divergence [PDF]
EntropyMotivated by questions arising at the intersection of information theory and geometry, we compare two dissimilarity measures between finite categorical distributions.
Arseniy Akopyan +3 more
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JS-MA: A Jensen-Shannon Divergence Based Method for Mapping Genome-Wide Associations on Multiple Diseases [PDF]
Frontiers in Genetics, 2020 Taking advantage of the high-throughput genotyping technology of Single Nucleotide Polymorphism (SNP), Genome-Wide Association Studies (GWASs) have been successfully implemented for defining the relative role of genes and the environment in disease risk,
Xuan Guo
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Fault Detection Based on Multi-Dimensional KDE and Jensen–Shannon Divergence [PDF]
Entropy, 2021 Weak fault signals, high coupling data, and unknown faults commonly exist in fault diagnosis systems, causing low detection and identification performance of fault diagnosis methods based on T2 statistics or cross entropy. This paper proposes a new fault
Juhui Wei +4 more
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Learning geometric Jensen-Shannon divergence for tiny object detection in remote sensing images [PDF]
Frontiers in Neurorobotics, 2023 Tiny objects in remote sensing images only have a few pixels, and the detection difficulty is much higher than that of regular objects. General object detectors lack effective extraction of tiny object features, and are sensitive to the Intersection-over-
Shuyan Ni +7 more
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Identifying Critical States of Complex Diseases by Single-Sample Jensen-Shannon Divergence [PDF]
Frontiers in Oncology, 2021 MotivationThe evolution of complex diseases can be modeled as a time-dependent nonlinear dynamic system, and its progression can be divided into three states, i.e., the normal state, the pre-disease state and the disease state.
Jinling Yan +7 more
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Noise Reduction Using Singular Value Decomposition with Jensen–Shannon Divergence for Coronary Computed Tomography Angiography [PDF]
Diagnostics, 2023 Coronary computed tomography angiography (CCTA) is widely used due to its improvements in computed tomography (CT) diagnostic performance. Unlike other CT examinations, CCTA requires shorter rotation times of the X-ray tube, improving the temporal ...
Ryosuke Kasai, Hideki Otsuka
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Bluetooth Device Identification Using RF Fingerprinting and Jensen-Shannon Divergence [PDF]
SensorsThe proliferation of radio frequency (RF) devices in contemporary society, especially in the fields of smart homes, Internet of Things (IoT) gadgets, and smartphones, underscores the urgent need for robust identification methods to strengthen ...
Rene Francisco Santana-Cruz +4 more
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Protein–ligand affinity prediction via Jensen-Shannon divergence of molecular dynamics simulation trajectories [PDF]
Biophysics and PhysicobiologyPredicting the binding affinity between proteins and ligands is a critical task in drug discovery. Although various computational methods have been proposed to estimate ligand target affinity, the method of Yasuda et al.
Kodai Igarashi, Masahito Ohue
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Granger Causality and Jensen–Shannon Divergence to Determine Dominant Atrial Area in Atrial Fibrillation [PDF]
Entropy, 2018 Atrial fibrillation (AF) is already the most commonly occurring arrhythmia. Catheter pulmonary vein ablation has emerged as a treatment that is able to make the arrhythmia disappear; nevertheless, recurrence to arrhythmia is very frequent. In this study,
Raquel Cervigón +4 more
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