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05/07/2023
Disentangled Multi-Fidelity Deep Bayesian Active Learning
To balance quality and cost, various domain areas of science and enginee...
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12/17/2022
Characterizing collective physical distancing in the U.S. during the first nine months of the COVID-19 pandemic
The COVID-19 pandemic offers an unprecedented natural experiment providi...
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06/10/2022
Multi-fidelity Hierarchical Neural Processes
Science and engineering fields use computer simulation extensively. Thes...
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06/05/2021
Accelerating Stochastic Simulation with Interactive Neural Processes
Stochastic simulations such as large-scale, spatiotemporal, age-structur...
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05/25/2021
Quantifying Uncertainty in Deep Spatiotemporal Forecasting
Deep learning is gaining increasing popularity for spatiotemporal foreca...
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02/12/2021
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting
We introduce DeepGLEAM, a hybrid model for COVID-19 forecasting. DeepGLE...
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07/01/2020
An Early Warning Approach to Monitor COVID-19 Activity with Multiple Digital Traces in Near Real-Time
Non-pharmaceutical interventions (NPIs) have been crucial in curbing COV...
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06/21/2020
Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
Locating the source of an epidemic, or patient zero (P0), can provide cr...
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04/08/2020