Ryan Lagerquist

发表

Quasi-Operational Testing of Real-Time Storm-Longevity Prediction via Machine Learning

Amy McGovern, Christopher D. Karstens, Travis M. Smith, 2019, Weather and Forecasting.

Deep Learning on Three-Dimensional Multiscale Data for Next-Hour Tornado Prediction

Amy McGovern, Travis M. Smith, Ryan Lagerquist, 2020, Monthly Weather Review.

Peering inside the black box: Using deep learning to improve understanding of weather phenomena

Amy McGovern, Ryan Lagerquist, David John Gagne, 2019 .

Tutorial on Machine Learning and Deep Learning for the Environmental and Geosciences

Karthik Kashinath, Prabhat, Anuj Karpatne, 2019 .

Using Deep Learning to Improve Prediction and Understanding of High-impact Weather

Ryan Lagerquist, Ryan Lagerquist, 2020 .

Emerging Data Science and Machine Learning Opportunities in the Weather and Climate Sciences

Karthik Kashinath, Anuj Karpatne, Kevin A. Reed, 2018 .

Machine Learning for Real-time Prediction of Damaging Straight-line Winds

Ryan Lagerquist, 2016 .

Deep Learning for Spatially Explicit Prediction of Synoptic-Scale Fronts

Amy McGovern, Ryan Lagerquist, David John Gagne, 2019, Weather and Forecasting.

Classifying Convective Storms Using Machine Learning

Amy McGovern, Travis M. Smith, Ryan Lagerquist, 2019, Weather and Forecasting.

Making the Black Box More Transparent: Understanding the Physical Implications of Machine Learning

Amy McGovern, Travis M. Smith, Ryan Lagerquist, 2019, Bulletin of the American Meteorological Society.

Using Machine Learning to Predict Damaging Straight-line Convective Winds

Ryan Lagerquist, Ryan Lagerquist, 2016 .

Using deep learning to emulate and accelerate a radiative-transfer model

Imme Ebert-Uphoff, Ryan Lagerquist, Jebb Stewart, 2021, Journal of Atmospheric and Oceanic Technology.

CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences - Version 1 pdf

Imme Ebert-Uphoff, Jebb Q. Stewart, Yoonjin Lee, 2021, ArXiv.