no code implementations • 22 Sep 2023 • Willa Potosnak, Cristian Challu, Kin G. Olivares, Artur Dubrawski
Our global-local architecture improves over patient-specific models by 9. 2-14. 6%.
3 code implementations • 15 Apr 2022 • Chirag Nagpal, Willa Potosnak, Artur Dubrawski
Applications of machine learning in healthcare often require working with time-to-event prediction tasks including prognostication of an adverse event, re-hospitalization or death.
2 code implementations • 11 Apr 2021 • Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek, Willa Potosnak, Suyash Bire, Salomey Osei, Björn Lütjens
In comparison, graph neural networks (GNNs) are capable of modeling large-scale spatial dependencies and are more interpretable due to the explicit modeling of information flow through edge connections.
1 code implementation • 2 Dec 2020 • Salva Rühling Cachay, Emma Erickson, Arthur Fender C. Bucker, Ernest Pokropek, Willa Potosnak, Salomey Osei, Björn Lütjens
Deep learning-based models have recently outperformed state-of-the-art seasonal forecasting models, such as for predicting El Ni\~no-Southern Oscillation (ENSO).
Multivariate Time Series Forecasting Spatio-Temporal Forecasting