I'm implementing the basic architecture from this paper: https://arxiv.org/pdf/1705.08260.pdf in PyTorch. It consists of an autoencoder and Spatial Transformer.
transform-stream
atlassian-crowd
recursive-datastructures
vungle-ads
android-jetpack-compose-testing
flask-pymongo
queryover
log4cxx
axios-retry
checkpointing
ensemble-learning
google-cloud-spanner
google-noto
object-property
oracle-spatial
multiple-instances
react-final-form-arrays
ngx-http-rewrite-module
github-classroom
parallel.foreachasync
translucency
organizational-chart
asyncvalue
android-hardware-keyboard
pyzmail
chrome-options
auto-value
powershell-remoting
x-ipfs-path
cllocationmanager