FALCON is a novel conformal prediction technique that learns locally calibrated confidence intervals for neural network surrogates modeling LHC scattering amplitudes.
The Les Houches Accord PDFs (LHAPDF) and Lhaglue
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
abstract
We describe the development of the LHAPDF library from its initial implementation following the Les Houches meeting in 2001 to its present state as a functional replacement for PDFLIB. Brief details are given of how to install and use the library together with the PDF sets available. We also describe LHAGLUE, an add-on PDFLIB look-a-like interface to LHAPDF, which facilitates using LHAPDF with existing Monte Carlo generators such as PYTHIA and HERWIG.
citation-role summary
background 1
method 1
citation-polarity summary
fields
hep-ph 2representative citing papers
PYTHIA 8.2 is a mature C++ event generator that combines hard processes, parton showers, multiparton interactions, and string fragmentation into a complete simulation framework for high-energy collisions.
citing papers explorer
-
Local Conformal Predictions for Calibrated Surrogates
FALCON is a novel conformal prediction technique that learns locally calibrated confidence intervals for neural network surrogates modeling LHC scattering amplitudes.
-
An Introduction to PYTHIA 8.2
PYTHIA 8.2 is a mature C++ event generator that combines hard processes, parton showers, multiparton interactions, and string fragmentation into a complete simulation framework for high-energy collisions.