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20222026
most citedFEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting

551 citations · 847 across the 23 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.LG2024

Maximizing the Impact of Deep Learning on Subseasonal-to-Seasonal Climate Forecasting: The Essential Role of Optimization

Yizhen Guo, Tian Zhou, Wanyi Jiang +3

Weather and climate forecasting is vital for sectors such as agriculture and disaster management. Although numerical weather prediction (NWP) systems have advanced, forecasting at…

cs.LG2024

Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting

Peiyuan Liu, Tian Zhou, Liang Sun +1

In the field of weather forecasting, traditional models often grapple with discretization errors and time-dependent source discrepancies, which limit their predictive performance.…

cs.LG2024★ 2 cited

SAttention: Improving Long Sequence Attention with Smoothed Skeleton Sketching

Xue Wang, Tian Zhou, Jianqing Zhu +6

Attention based models have achieved many remarkable breakthroughs in numerous applications. However, the quadratic complexity of Attention makes the vanilla Attention based models…

cs.LG2024★ 1 cited

Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting

Yanjun Zhao, Tian Zhou, Chao Chen +3

Time series analysis is vital for numerous applications, and transformers have become increasingly prominent in this domain. Leading methods customize the transformer architecture…

cs.LG2024

FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting

Ziqing Ma, Wenwei Wang, Tian Zhou +4

Accurate solar power forecasting is crucial to integrate photovoltaic plants into the electric grid, schedule and secure the power grid safety. This problem becomes more demanding…

cs.LG2024★ 2 cited

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…