In this section
@inproceedings{Nadler:2020:10.3233/APC200025,
author = {Nadler, P and Arcucci, R and Guo, Y-K},
doi = {10.3233/APC200025},
pages = {59--68},
publisher = {IOS PRESS},
title = {A Scalable Approach to Econometric Inference},
url = {http://dx.doi.org/10.3233/APC200025},
year = {2020}
}
TY - CPAPER
AU - Nadler,P
AU - Arcucci,R
AU - Guo,Y-K
DO - 10.3233/APC200025
EP - 68
PB - IOS PRESS
PY - 2020///
SN - 0927-5452
SP - 59
TI - A Scalable Approach to Econometric Inference
UR - http://dx.doi.org/10.3233/APC200025
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000624288400006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
ER -
Artificial Intelligence Network
South Kensington Campus
Imperial College London
SW7 2AZ
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