8 citations · 15 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 7 cited
Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju +3
We introduce a novel loss function, Covariance Loss, which is conceptually equivalent to conditional neural processes and has a form of regularization so that is applicable to many…
physics.geo-ph2020★ 8 cited
Improving seasonal forecast using probabilistic deep learning
Baoxiang Pan, Gemma J. Anderson, AndrE Goncalves +3
The path toward realizing the potential of seasonal forecasting and its socioeconomic benefits depends heavily on improving general circulation model based dynamical forecasting sy…