Liyao Gao
University of Washington(US)
Publications by Year
Research Areas
Gaussian Processes and Bayesian Inference, Advanced Neural Network Applications, COVID-19 epidemiological studies, Stochastic Gradient Optimization Techniques, Neural Networks and Applications
Most-Cited Works
- → Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States(2022)304 cited
- → The United States COVID-19 Forecast Hub dataset(2022)123 cited
- → Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US(2021)77 cited
- → Quantifying Uncertainty in Deep Spatiotemporal Forecasting(2021)54 cited
- → H-DrunkWalk(2020)39 cited
- → Non-convex Learning via Replica Exchange Stochastic Gradient MCMC(2020)20 cited
- → DeepGLEAM: A hybrid mechanistic and deep learning model for COVID-19 forecasting(2021)19 cited
- → Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants(2024)11 cited
- → On Optimal Early Stopping: Over-informative versus Under-informative Parametrization(2022)7 cited