118 citations · 126 across the 8 of their papers we have counts for
8 papers · 1 filter
Pushing the Limits of High-Resolution Weather Forecasting through Data Scaling
Yang Zhao, Peisong Niu, Tian Zhou +5
The development of 0.1 global weather forecasting models based on machine learning (ML) is constrained by the limited availability of high-resolution data, as decades of…
Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting
Ziqing Ma, Kai Ying, Xinyue Gu +7
Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging due to the pronounced diurnal cycle a…
Enhancing AI-Based Tropical Cyclone Track and Intensity Forecasting via Systematic Bias Correction
Peisong Niu, Haifan Zhang, Yang Zhao +6
Tropical cyclones (TCs) pose severe threats to life, infrastructure, and economies in tropical and subtropical regions, underscoring the critical need for accurate and timely forec…
Target Concept Tuning Improves Extreme Weather Forecasting
Shijie Ren, Xinyue Gu, Ziheng Peng +6
Deep learning models for meteorological forecasting often fail in rare but high-impact events such as typhoons, where relevant data is scarce. Existing fine-tuning methods typicall…
Utilizing Strategic Pre-training to Reduce Overfitting: Baguan -- A Pre-trained Weather Forecasting Model
Peisong Niu, Ziqing Ma, Tian Zhou +4
Weather forecasting has long posed a significant challenge for humanity. While recent AI-based models have surpassed traditional numerical weather prediction (NWP) methods in globa…
Attention as Robust Representation for Time Series Forecasting
PeiSong Niu, Tian Zhou, Xue Wang +2
Time series forecasting is essential for many practical applications, with the adoption of transformer-based models on the rise due to their impressive performance in NLP and CV. T…
Understanding the Role of Textual Prompts in LLM for Time Series Forecasting: an Adapter View
Peisong Niu, Tian Zhou, Xue Wang +2
In the burgeoning domain of Large Language Models (LLMs), there is a growing interest in applying LLM to time series forecasting, with multiple studies focused on leveraging textua…
One Fits All:Power General Time Series Analysis by Pretrained LM
Tian Zhou, PeiSong Niu, Xue Wang +2
Although we have witnessed great success of pre-trained models in natural language processing (NLP) and computer vision (CV), limited progress has been made for general time series…