Near-real-time Earthquake-induced Fatality Estimation using Crowdsourced Data and Large-Language Models

no code implementations • 4 Dec 2023 • Chenguang Wang, Davis Engler, Xuechun Li, James Hou, David J. Wald, Kishor Jaiswal, Susu Xu

Traditional systems for estimating human loss in disasters often depend on manually collected early casualty reports from global media, a process that's labor-intensive and slow with notable time delays.

Few-Shot Learning

Normalizing flow-based deep variational Bayesian network for seismic multi-hazards and impacts estimation from InSAR imagery

no code implementations • 20 Oct 2023 • Xuechun Li, Paula M. Burgi, Wei Ma, Hae Young Noh, David J. Wald, Susu Xu

Onsite disasters like earthquakes can trigger cascading hazards and impacts, such as landslides and infrastructure damage, leading to catastrophic losses; thus, rapid and accurate estimates are crucial for timely and effective post-disaster responses.

Variational Inference