most citedIdentifying Precipitation Regimes in China Using Model-Based Clustering of Spatial Functional Data

5 citations · 5 across the 1 of their papers we have counts for

collaborators

2 papers

stat.AP2019★ 5 cited

Identifying Precipitation Regimes in China Using Model-Based Clustering of Spatial Functional Data

Haozhe Zhang, Zhengyuan Zhu, Shuiqing Yin

The identification of precipitation regimes is important for many purposes such as agricultural planning, water resource management, and return period estimation. Since precipitati…

physics.ao-ph2018

Dimensionality-Reduction of Climate Data using Deep Autoencoders

J. A. Saenz, N. Lubbers, N. M. Urban

We explore the use of deep neural networks for nonlinear dimensionality reduction in climate applications. We train convolutional autoencoders (CAEs) to encode two temperature fiel…