614 citations · 773 across the 7 of their papers we have counts for
7 papers
STLDM: Spatio-Temporal Latent Diffusion Model for Precipitation Nowcasting
Shi Quan Foo, Chi-Ho Wong, Zhihan Gao +3
Precipitation nowcasting is a critical spatio-temporal prediction task for society to prevent severe damage owing to extreme weather events. Despite the advances in this field, the…
PreDiff: Precipitation Nowcasting with Latent Diffusion Models
Zhihan Gao, Xingjian Shi, Boran Han +6
Earth system forecasting has traditionally relied on complex physical models that are computationally expensive and require significant domain expertise. In the past decade, the un…
Multi-modal learning for geospatial vegetation forecasting
Vitus Benson, Claire Robin, Christian Requena-Mesa +7
The innovative application of precise geospatial vegetation forecasting holds immense potential across diverse sectors, including agriculture, forestry, humanitarian aid, and carbo…
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
Zhihan Gao, Xingjian Shi, Hao Wang +4
Conventionally, Earth system (e.g., weather and climate) forecasting relies on numerical simulation with complex physical models and are hence both expensive in computation and dem…
Fully Using Classifiers for Weakly Supervised Semantic Segmentation with Modified Cues
Ting Sun, Lei Tai, Zhihan Gao +2
This paper proposes a novel weakly-supervised semantic segmentation method using image-level label only. The class-specific activation maps from the well-trained classifiers are us…
Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
Xingjian Shi, Zhihan Gao, Leonard Lausen +4
With the goal of making high-resolution forecasts of regional rainfall, precipitation nowcasting has become an important and fundamental technology underlying various public servic…
Approximating Minimum-Cost Connected T-Joins
Joseph Cheriyan, Zachary Friggstad, Zhihan Gao
We design and analyse approximation algorithms for the minimum-cost connected T-join problem: given an undirected graph G = (V;E) with nonnegative costs on the edges, and a subset…