1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Accelerating Domain-aware Deep Learning Models with Distributed Training
Aishwarya Sarkar, Chaoqun Lu, Ali Jannesari
Recent advances in data-generating techniques led to an explosive growth of geo-spatiotemporal data. In domains such as hydrology, ecology, and transportation, interpreting the com…
cs.LG2021
Transfer Learning Approaches for Knowledge Discovery in Grid-based Geo-Spatiotemporal Data
Aishwarya Sarkar, Jien Zhang, Chaoqun Lu +1
Extracting and meticulously analyzing geo-spatiotemporal features is crucial to recognize intricate underlying causes of natural events, such as floods. Limited evidence about hidd…
cs.LG2020
HydroDeep -- A Knowledge Guided Deep Neural Network for Geo-Spatiotemporal Data Analysis
Aishwarya Sarkar, Jien Zhang, Chaoqun Lu +1
Due to limited evidence and complex causes of regional climate change, the confidence in predicting fluvial floods remains low. Understanding the fundamental mechanisms intrinsic t…