R. Lily Hu

According to our database, R. Lily Hu authored at least 13 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Next Day Wildfire Spread: A Machine Learning Dataset to Predict Wildfire Spreading From Remote-Sensing Data.

Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, Yi-Fan Chen

IEEE Trans. Geosci. Remote. Sens., 2022

Accelerating physics simulations with tensor processing units: An inundation modeling example.

R. Lily Hu, Damien Pierce, Yusef Shafi, Anudhyan Boral, Vladimir Anisimov, Sella Nevo, Yi-Fan Chen

Int. J. High Perform. Comput. Appl., 2022

Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior.

John Burge, Matthew R. Bonanni, R. Lily Hu, Matthias Ihme

CoRR, 2022

Accelerating Physics Simulations with TPUs: An Inundation Modeling Example.

Damien Pierce, R. Lily Hu, Yusef Shafi, Anudhyan Boral, Vladimir Anisimov, Sella Nevo, Yi-Fan Chen

CoRR, 2022

2021

Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data.

Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, Yi-Fan Chen

CoRR, 2021

Dynamic Placement of Rapidly Deployable Mobile Sensor Robots Using Machine Learning and Expected Value of Information.

Alice M. Agogino, Hae Young Jang, Vivek Rao, Ritik Batra, Felicity Liao, Rohan Sood, Irving Fang, R. Lily Hu, Emerson Shoichet-Bartus, John Matranga

CoRR, 2021

2020

A Mathematical Programming Formulation for Optimal Load Shifting of Electricity Demand for the Smart Grid.

R. Lily Hu, Ryan Skorupski, Robert Entriken, Yinyu Ye

IEEE Trans. Big Data, 2020

Convolutional LSTM Neural Networks for Modeling Wildland Fire Dynamics.

John Burge, Matthew Bonanni, Matthias Ihme, R. Lily Hu

CoRR, 2020

Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data.

Fantine Huot, R. Lily Hu, Matthias Ihme, Qing Wang, John Burge, Tianjian Lu, Jason Hickey, Yi-Fan Chen, John R. Anderson

CoRR, 2020

2017

Image Segmentation to Distinguish Between Overlapping Human Chromosomes.

R. Lily Hu, Jeremy Karnowski, Ross Fadely, Jean-Patrick Pommier

CoRR, 2017

2016

Machine Learning to Scale Fault Detection in Smart Energy Generation and Building Systems.

R. Lily Hu

PhD thesis, 2016

Diagnosing wind turbine faults using machine learning techniques applied to operational data.

Kevin Leahy, R. Lily Hu, Ioannis C. Konstantakopoulos, Costas J. Spanos, Alice M. Agogino

Proceedings of the IEEE International Conference on Prognostics and Health Management, 2016

Using Domain Knowledge Features for Wind Turbine Diagnostics.

R. Lily Hu, Kevin Leahy, Ioannis C. Konstantakopoulos, David M. Auslander, Costas J. Spanos, Alice M. Agogino

Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016