Research
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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,695 papers · 148 categories

Trend · papers per month

count% of corpus
0111 · Jun 201919922001200920172026
4 results for “low-count”
Low-count Time Series Anomaly Detectioncs.LG

We tackle anomaly detection in sparse time series data.

problem Sparse time series with low signal-to-noise ratios and non-uniform performance.
method We introduce a novel generative procedure for benchmark datasets and demonstrate how anomaly score smoothing improves performance.
result Anomaly score smoothing consistently improves performance in low-count time series anomaly detection.
time series anomaly detectionsparse datalow-countanomaly score smoothingbenchmark datasets
2023-08-24abs ↗pdf ↗
Machine Learning in Quantitative PET Imagingeess.IV

This paper reviewed the machine learning-based studies for quantitative positron emission tomography (PET). Specifically, we summarized the recent developments of machine learning-based methods in PET attenuation correction and low-count PET reconstruction by listing and comparing the proposed methods, study designs an…

2020-01-18abs ↗pdf ↗
Probabilistic Canonical Correlation Analysis for Sparse Count Datastat.ME

Proposes PSCCA for estimating correlations and canonical correlations in sparse count data.

problem Estimating correlations and canonical correlations in sparse count data from next-generation sequencing.
method Probabilistic approach for sparse count data sets (PSCCA).
result PSCCA outperforms other methods in estimating true correlations and canonical correlations at the natural parameter level.
Canonical correlationSparse count dataProbabilistic approachNext-generation sequencingMicroRNA
2020-05-11abs ↗pdf ↗