5 citations · 6 across the 3 of their papers we have counts for
3 papers
Tackling water table depth modeling via machine learning: From proxy observations to verifiability
Joseph Janssen, Ardalan Tootchi, Ali A. Ameli
Spatial patterns of water table depth (WTD) play a crucial role in shaping ecological resilience, hydrological connectivity, and human-centric systems. Generally, a large-scale (e.…
A Gaussian Sliding Windows Regression Model for Hydrological Inference
Stefan Schrunner, Parham Pishrobat, Joseph Janssen +4
Statistical models are an essential tool to model, forecast and understand the hydrological processes in watersheds. In particular, the understanding of time lags associated with t…
Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science
Joseph Janssen, Shizhe Meng, Asad Haris +5
Scientists and statisticians often want to learn about the complex relationships that connect two time-varying variables. Recent work on sparse functional historical linear models…