56 citations · 79 across the 5 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.SI2018★ 3 cited
Multivariate Spatiotemporal Hawkes Processes and Network Reconstruction
Baichuan Yuan, Hao Li, Andrea L. Bertozzi +2
There is often latent network structure in spatial and temporal data and the tools of network analysis can yield fascinating insights into such data. In this paper, we develop a no…
eess.SP2018★ 1 cited
Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study using CO2-driven Cold-Water Geyser in Chimayo, New Mexico
B. Yuan, Y. J. Tan, M. K. Mudunuru +8
We present an approach based on machine learning (ML) to distinguish eruption and precursory signals of Chimayó geyser (New Mexico, USA) under noisy environments. This geyser can b…
cs.LG2018★ 56 cited
Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data
Bao Wang, Xiyang Luo, Fangbo Zhang +3
We present a generic framework for spatio-temporal (ST) data modeling, analysis, and forecasting, with a special focus on data that is sparse in both space and time. Our multi-scal…