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Robust Causality and False Attribution in Data-Driven Earth Science Discoveries
Elizabeth Eldhose, Tejasvi Chauhan, Vikram Chandel +2
Causal and attribution studies are essential for earth scientific discoveries and critical for informing climate, ecology, and water policies. However, the current generation of me…
Ad Hoc Teamwork in the Presence of Adversaries
Ted Fujimoto, Samrat Chatterjee, Auroop Ganguly
Advances in ad hoc teamwork have the potential to create agents that collaborate robustly in real-world applications. Agents deployed in the real world, however, are vulnerable to…
Predictions of damages from Atlantic tropical cyclones: a hierarchical Bayesian study on extremes
Lindsey Dietz, Sakshi Arya, Vishal Subedi +2
Bayesian hierarchical models are proposed for modeling tropical cyclone characteristics and their damage potential in the Atlantic basin. We model the joint probability distributio…
Deep Transfer Learning on Satellite Imagery Improves Air Quality Estimates in Developing Nations
Nishant Yadav, Meytar Sorek-Hamer, Michael Von Pohle +9
Urban air pollution is a public health challenge in low- and middle-income countries (LMICs). However, LMICs lack adequate air quality (AQ) monitoring infrastructure. A persistent…
Climate-mediated shifts in temperature fluctuations promote extinction risk
Kate Duffy, Tarik C. Gouhier, Auroop R. Ganguly
Climate-mediated changes in the spatiotemporal distribution of thermal stress can destabilize animal populations and promote extinction risk. Using quantile, spectral, and wavelet…
Explainable deep learning for insights in El Niño and river flows
Yumin Liu, Kate Duffy, Jennifer G. Dy +1
The El Niño Southern Oscillation (ENSO) is a semi-periodic fluctuation in sea surface temperature (SST) over the tropical central and eastern Pacific Ocean that influences interann…