1 citations · 1 across the 3 of their papers we have counts for
6 papers
CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching
Xingjian Wu, Xiangfei Qiu, Zhengyu Li +5
Anomaly detection in multivariate time series is challenging as heterogeneous subsequence anomalies may occur. Reconstruction-based methods, which focus on learning normal patterns…
TimeRFT: Stimulating Generalizable Time Series Forecasting for TSFMs via Reinforcement Finetuning
Siyang Li, Yize Chen, Zijie Zhu +4
Time Series Foundation Models (TSFMs) have demonstrated strong generalization capability and data efficiency in time series forecasting through large-scale pretraining. However, ad…
Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
Fanpu Cao, Lu Dai, Jindong Han +1
Multivariate time series forecasting (MTSF) plays a vital role in numerous real-world applications, yet existing models remain constrained by their reliance on a limited historical…
PISA: Piecewise Sparse Attention Is Wiser for Efficient Diffusion Transformers
Haopeng Li, Shitong Shao, Wenliang Zhong +4
Diffusion Transformers are fundamental for video and image generation, but their efficiency is bottlenecked by the quadratic complexity of attention. While block sparse attention a…
OccamVTS: Distilling Vision Models to 1% Parameters for Time Series Forecasting
Sisuo Lyu, Siru Zhong, Weilin Ruan +4
Time series forecasting is fundamental to diverse applications, with recent approaches leverage large vision models (LVMs) to capture temporal patterns through visual representatio…
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
Jinliang Deng, Feiyang Ye, Du Yin +3
Long-term time series forecasting (LTSF) represents a critical frontier in time series analysis, characterized by extensive input sequences, as opposed to the shorter spans typical…