FRB 20250316A is confirmed as a pronounced outlier whose peak flux and fluence imply return periods of roughly 30-800 years and 8-55 years respectively under GEV modeling of the CHIME catalog.
Unsupervised methods
3 Pith papers cite this work, alongside 35 external citations. Polarity classification is still indexing.
3
Pith papers citing it
35
external citations · OpenAlex
representative citing papers
Frabjous applies deep learning to classify FRB morphologies into five classes at 55% accuracy by augmenting limited real data with simulations.
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.
citing papers explorer
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Extreme-Value Distribution Analysis of the Second CHIME/FRB Catalog: Assessing the Rarity of the One-off FRB 20250316A
FRB 20250316A is confirmed as a pronounced outlier whose peak flux and fluence imply return periods of roughly 30-800 years and 8-55 years respectively under GEV modeling of the CHIME catalog.
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Frabjous: Deep Learning Fast Radio Burst Morphologies
Frabjous applies deep learning to classify FRB morphologies into five classes at 55% accuracy by augmenting limited real data with simulations.
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Robustness Analysis of USmorph: II. Optimizing Feature Extraction, Dimensionality Reduction, and Clustering for Unsupervised Galaxy Morphology Classification
Optimizes ImageNet-pretrained AlexNet, UMAP, and a bagging multi-cluster voting scheme with K-means, Birch and Agg for unsupervised galaxy morphology classification, reporting improved stability and consistency with galaxy evolution expectations.