From the 1 of 51 linked papers with an AI index.
2.2k citations · 7.8k across the 48 of their papers we have counts for
10 papers · 1 filter
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models
Eric Zelikman, Sharon Zhou, Jeremy Irvin +7
Advancing probabilistic solar forecasting methods is essential to supporting the integration of solar energy into the electricity grid. In this work, we develop a variety of state-…
NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Yi Ding +4
We present Natural Gradient Boosting (NGBoost), an algorithm for generic probabilistic prediction via gradient boosting. Typical regression models return a point estimate, conditio…
Predicting Inpatient Discharge Prioritization With Electronic Health Records
Anand Avati, Stephen Pfohl, Chris Lin +7
The paper develops machine‑learning models using eight years of Stanford Hospital electronic health records to predict which inpatients will be discharged within the next 24 hours,…
Countdown Regression: Sharp and Calibrated Survival Predictions
Anand Avati, Tony Duan, Sharon Zhou +3
Probabilistic survival predictions from models trained with Maximum Likelihood Estimation (MLE) can have high, and sometimes unacceptably high variance. The field of meteorology, w…
Data Noising as Smoothing in Neural Network Language Models
Ziang Xie, Sida I. Wang, Jiwei Li +4
Data noising is an effective technique for regularizing neural network models. While noising is widely adopted in application domains such as vision and speech, commonly used noisi…
Tuned Models of Peer Assessment in MOOCs
Chris Piech, Jonathan Huang, Zhenghao Chen +3
In massive open online courses (MOOCs), peer grading serves as a critical tool for scaling the grading of complex, open-ended assignments to courses with tens or hundreds of thousa…