Search Results for author:
Found 2 papers, 1 papers with code
Enhancing Uncertain Demand Prediction in Hospitals Using Simple and Advanced Machine Learning
Accurately predicting patient care demand, however, is a ubiquitous challenge for hospitals across the world due, in part, to the demand's time-varying temporal variability, and, in part, to the difficulty in modelling trends in advance.
Forecasting the 2016-2017 Central Apennines Earthquake Sequence with a Neural Point Process
We investigate whether these flexible point process models can be applied to short-term seismicity forecasting by extending an existing temporal neural model to the magnitude domain and we show how this model can forecast earthquakes above a target magnitude threshold.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
