- Is Artificial Intelligence Providing the Second Revolution for Weather Forecasting, arxiv 2024
- Challenges and design choices for global weather and climate models based on machine learning, GMD 2018
- Improving Data-Driven Global Weather Prediction UsingDeep Convolutional Neural Networks on a Cubed Sphere, JAMES 2020
- FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators, arxiv 2022
- Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast, Nature 2023
- GraphCast: Learning skillful medium-range global weather forecasting, Science 2023
- FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead, arxiv 2023
- FuXi: A cascade machine learning forecasting system for 15-day global weather forecast, arxiv 2023
- The rise of data-driven weather forecasting, arxiv 2023
- ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast, arxiv 2024
- FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting, arxiv 2024
- FENGWU-4DVAR: COUPLING THE DATA-DRIVEN WEATHER FORECASTING MODEL WITH 4D VARIATIONAL ASSIMILATION, ICML 2024
- Towards an End-to-End Artificial Intelligence Driven Global Weather Forecasting System, arixv 2023
- Aardvark Weather: end-to-end data-driven weather forecasting, arxiv 2024
- Deep Generative Data Assimilation in Multimodal Setting, arxiv 2024
- Fuxi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations, arxiv 2024
- Scalable Data Assimilation with Message Passing, Environmental Data Science, 2024
- Assessing the Feasibility of an NWP Satellite Data Assimilation System Entirely Based on AI Techniques, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024
- CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling
- Skilful nowcasting of extreme precipitation with NowcastNet, Nature 2023
- Deep learning for multi-year ENSO forecasts
- Multi-task machine learning improves multi- seasonal prediction of the Indian Ocean Dipole
- Exploring dominant processes for multi-month MJO prediction using deep learning
- Seasonal Arctic sea ice forecasting with probabilistic deep learning
- Early warning signal for a tipping point suggested by a millennial Atlantic Multidecadal Variability reconstruction
- Neural-Network Parameterization of Subgrid Momentum Transport in the Atmosphere, JAMES 2023
- Neural Network Parameterization of Subgrid-Scale Physics From a Realistic Geography Global Storm-Resolving Simulation, JAMES 2024
- Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44,
- High-resolution downscaling with interpretable deep learning: Rainfall extremes over New Zealand, Weather and Climate Extremes, 2022 (Q1).
- Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method, arxiv 2024
- Uncertainty Quantification for Traffic Forecasting: A Unified Approach, ICDE 2023
- Spatiotemporal forecasting in earth system science: Methods, uncertainties, predictability and future directions, Earth-Science Reviews, 2021 (Q1).
- auxiliary learning with joint task and data scheduling
- Reversible Column Networks
AAAI 2023 related (https://aaai-23.aaai.org/wp-content/uploads/2023/01/Updated_AAAI-23-Technical-Schedule-FEB09.pdf)
- Counterfactual Dynamics Forecasting - A New Setting of Quantitative Reasoning
- An Extreme-Adaptive Time Series Prediction Model Based on Probability
- Opposite Online Learning via Sequentially Integrated Stochastic Gradient
- Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting
- WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series
- Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
- Improving Uncertainty Quantification of Deep Classifiers via Neighborhood Conformal Prediction: Novel Algorithm and Theoretical Analysis