activity
20192025
most citedPangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

127 citations · 233 across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Resolving sources of uncertainty in AI weather forecasting

Wenbo Hu, Xinlei Xiong, Shuxun Zhou +5

Weather forecast uncertainty arises from imperfect analyses and forecast models, but ensemble spread alone does not reveal how distinct sources relate to downstream targets. We int…

cs.CV2023★ 5 cited

Towards AGI in Computer Vision: Lessons Learned from GPT and Large Language Models

Lingxi Xie, Longhui Wei, Xiaopeng Zhang +4

The AI community has been pursuing algorithms known as artificial general intelligence (AGI) that apply to any kind of real-world problem. Recently, chat systems powered by large l…

cs.DC2023

Pipeline MoE: A Flexible MoE Implementation with Pipeline Parallelism

Xin Chen, Hengheng Zhang, Xiaotao Gu +3

The Mixture of Experts (MoE) model becomes an important choice of large language models nowadays because of its scalability with sublinear computational complexity for training and…

physics.ao-ph2022★ 127 cited

Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

Kaifeng Bi, Lingxi Xie, Hengheng Zhang +3

In this paper, we present Pangu-Weather, a deep learning based system for fast and accurate global weather forecast. For this purpose, we establish a data-driven environment by dow…

cs.CV2020★ 28 cited

Weight-Sharing Neural Architecture Search: A Battle to Shrink the Optimization Gap

Lingxi Xie, Xin Chen, Kaifeng Bi +8

Neural architecture search (NAS) has attracted increasing attentions in both academia and industry. In the early age, researchers mostly applied individual search methods which sam…

cs.CV2020★ 29 cited

GOLD-NAS: Gradual, One-Level, Differentiable

Kaifeng Bi, Lingxi Xie, Xin Chen +2

There has been a large literature of neural architecture search, but most existing work made use of heuristic rules that largely constrained the search flexibility. In this paper,…

cs.LG2019★ 44 cited

Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters

Kaifeng Bi, Changping Hu, Lingxi Xie +3

DARTS is a popular algorithm for neural architecture search (NAS). Despite its great advantage in search efficiency, DARTS often suffers weak stability, which reflects in the large…