- 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).
- 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