Survey

• [2022 Computers & Geosciences]A review of Earth Artificial Intelligencehttps://www.sciencedirect.com/science/article/pii/S0098300422000036

ST Models

• [2023 Neurips]Automatic Integration for Spatiotemporal Neural Point Processes
• [2023 KDD]Deep Bayesian Active Learning for Accelerating Stochastic Simulation

Hydrologic

• [2020 ICLR]Hydronets: Leveraging River Structure for Hydrologic Modeling
• [2020 Neurips]https://neuralhydrology.github.io/post/research/gauch2020neurips/
• [2020 Neurips]https://research.google/pubs/a-deep-learning-architecture-for-conservative-dynamical-systems-application-to-rainfall-runoff-modeling/
• [2020 Neurips]https://nips.cc/virtual/2020/20140
• [2020 Neurips]https://nips.cc/virtual/2020/20280
• [2021 Water Resources Research]What Role Does Hydrological Science Play in the Age of Machine Learning?
• [2021 SDM]Physics-guided recurrent graph model for predicting flow and temperature in river networks
• [2022 KDD]Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks

Weather and climate modeling

• [2024 Neurips]Probabilistic Emulation of a Global Climate Model with Spherical DYffusion

Example Proposals

• Physics Informed Graph Neural Network-based Snow Water Equivalent Forecasting https://www.nsf.gov/awardsearch/showAward?AWD_ID=2425687