Modelling systems with a mixture of I(d) and I(0) variables using the fractionally co-integrated VAR model
Sign Up to like & getrecommendations! Published in 2019 at "Economics Letters"
DOI: 10.1016/j.econlet.2019.05.031
Abstract: Abstract We propose a filtration technique for making inference in systems with I ( 0 ) and I ( d ) variables using the fractionally co-integrated vector autoregressive (FCVAR) model with long memory in the… read more here.
Keywords: variables using; using fractionally; fractionally integrated; model ... See more keywords
Active learning regularization increases clear sky retrieval rates for vegetation biophysical variables using Sentinel-2 data
Sign Up to like & getrecommendations! Published in 2021 at "Remote Sensing of Environment"
DOI: 10.1016/j.rse.2020.112241
Abstract: Abstract For typical cloud conditions, a clear sky retrieval rate (CSRR) >67% is required to meet the Global Climate Observing System temporal interval requirement of 10 days when mapping canopy biophysical variables (‘variables’). Physically based algorithms… read more here.
Keywords: sl2p; active learning; variables using; clear sky ... See more keywords
Constructing Collective Variables Using Invariant Learned Representations.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.2c00729
Abstract: On the time scales accessible to atomistic numerical modeling, chemical reactions are considered rare events. Therefore, the atomistic simulations are commonly biased along a low-dimensional representation of a chemical reaction in an atomic structure space,… read more here.
Keywords: constructing collective; learned representations; variables using; collective variables ... See more keywords