NeurIPS is one of the premier conferences on machine learning, and includes a wide audience of researchers and practitioners in academia, industry, and related fields. Four department PhD students had three first-authored Proposal Track papers accepted for the workshop Tackling Climate Change with Machine Learning, which will be held in December.
1) Trey McNeely and Nic Dalmasso with a Spotlight Talk (Proposal Track) on Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning (joint work with Kim Wood and Ann Lee)
2) Lorenzo Tomaselli with a Spotlight Talk (Proposal Track) on Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management (joint work with Coty Jen and Ann Lee)
3) Nic Dalmasso and Galen Vincent with a Poster (Proposal Track) on HECT: High-Dimensional Ensemble Consistency Testing for Climate Models (joint work with Dorit Hammerling and Ann Lee)