Research
On-device research index

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.

169,051 papers · 148 categories

Trend · papers per month

count% of corpus
0.3%0.5%0.8%0.1% · Jul 201919922001200920182026
2 results for “MadMiner”
MadMiner: Machine learning-based inference for particle physicshep-ph

MadMiner uses machine learning to analyze high-dimensional particle physics data.

problem Challenges in analyzing high-dimensional event data for subtle kinematic signatures.
method Combines matrix element information and machine learning to analyze particle physics data.
result New techniques substantially increase sensitivity to new physics.
particle physicsmachine learningkinematic signatureshigh-dimensional dataMadMiner
2019-07-24abs ↗pdf ↗
Effective LHC measurements with matrix elements and machine learninghep-ph

New methods combine matrix elements and machine learning for more accurate LHC measurements.

problem High-dimensional data and complex detector response make likelihood function estimation difficult.
method Review and application of traditional histogram, Matrix Element Method, Optimal Observables, and neural density estimation techniques. Use of MadMiner for automation.
result New techniques have the potential to substantially improve LHC measurement sensitivity.
LHCmatrix elementsmachine learninglikelihood functionneural density estimation
2019-06-04abs ↗pdf ↗