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.
New supervised and unsupervised NFLTs for elliptical distributions.
The paper introduces a new method to find meaningful data subsets in multivariate probability density functions.
Important information concerning a multivariate data set, such as clusters and modal regions, is contained in the derivatives of the probability density function. Despite this importance, nonparametric estimation of higher order derivatives of the density functions have received only relatively scant attention. Kernel …
Principal Components Analysis is a widely used technique for dimension reduction and characterization of variability in multivariate populations. Our interest lies in studying when and why the rotation to principal components can be used effectively within a response-predictor set relationship in the context of mode hu…
We leverage recent breakthroughs in neural density estimation to propose a new unsupervised anomaly detection technique (ANODE). By estimating the probability density of the data in a signal region and in sidebands, and interpolating the latter into the signal region, a likelihood ratio of data vs. background can be co…
Two methods use simulation to improve anomaly detection in particle physics.
Autoencoders misidentify anomalies due to data topology.
VAE improves anomaly detection for jet tagging at the LHC.
Machine-learned anomaly detection in new-physics searches needs calibration and look-elsewhere correction