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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.

169,181 papers · 148 categories

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0111 · May 201719922001200920182026
10 results for mosquitoes

Paper proposes cost-sensitive detection for environmental acoustic sensing.

problem Infeasibility of manual analysis for large-scale acoustic data.
method Cost-sensitive classification with variational autoencoders in Neyman-Pearson framework.
result Improved control over false positive and false negative rates.

Many real-world time-series analysis problems are characterised by scarce data. Solutions typically rely on hand-crafted features extracted from the time or frequency domain allied with classification or regression engines which condition on this (often low-dimensional) feature vector. The huge advances enjoyed by many…

2017-05-15abs ↗pdf ↗

Second order Sobolev metrics are a useful tool in the shape analysis of curves. In this paper we combine these metrics with varifold-based inexact matching to explore a new strategy of computing geodesics between unparametrized curves. We describe the numerical method used for solving the inexact matching problem, appl…

2017-06-06abs ↗pdf ↗

Enhanced Zika spread forecasting using topological data analysis.

problem Challenging prediction of Zika virus spread due to nonlinear spatio-temporal dependency and lack of historical records.
method Integrates topological data analysis, specifically persistent homology, into predictive machine learning models.
result Ensemble forecasting improves Zika spread predictions in Brazil.

BCCNet combines biased crowd labels to train classifiers for disaster response.

problem Improper labels from citizen scientists limit machine learning applications.
method Bayesian classifier combination neural network (BCCNet) aggregates and trains classifiers from imperfect labels.
result BCCNet effectively processes large unstructured data for disaster prevention and response.