A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations

Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review

Original language	German (Austria)
Title of host publication	Proceedings of 'A Virtual Tribute to Quark Confinement and the Hadron Spectrum', 2021
Publication status	Accepted/In press - 2021

Cite this

@inproceedings{548577e5e25348f8922a634c52ed2c97,

title = "A machine learning pipeline for autonomous numerical analytic continuation of Dyson-Schwinger equations",

author = "Andreas Windisch and Thomas Gallien and Schwarzlm{\"u}ller, {Christopher Hartwig}",

year = "2021",

language = "Deutsch ({\"O}sterreich)",

booktitle = "Proceedings of 'A Virtual Tribute to Quark Confinement and the Hadron Spectrum', 2021",

}

Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review