20 citations · 27 across the 8 of their papers we have counts for
6 papers · 1 filter
End-to-End Learning for Partially-Observed Time Series with PyPOTS
Wenjie Du, Yiyuan Yang, Tianxiang Zhan +1
Partially-observed time series (POTS) is ubiquitous in real-world applications, yet most existing toolchains separate missing-value handling from downstream learning, which limits…
Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback
Yiyuan Yang, Zichuan Liu, Lei Song +6
Time series anomaly detection (TSAD) has traditionally focused on binary classification and often lacks the fine-grained categorization and explanatory reasoning required for trans…
Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
Yaxuan Kong, Yiyuan Yang, Shiyu Wang +7
Understanding time series data is fundamental to many real-world applications. Recent work explores multimodal large language models (MLLMs) to enhance time series understanding wi…
TSI-Bench: Benchmarking Time Series Imputation
Wenjie Du, Jun Wang, Linglong Qian +12
Effective imputation is a crucial preprocessing step for time series analysis. Despite the development of numerous deep learning algorithms for time series imputation, the communit…
Beyond Random Missingness: Clinically Rethinking for Healthcare Time Series Imputation
Linglong Qian, Yiyuan Yang, Wenjie Du +3
This study investigates the impact of masking strategies on time series imputation models in healthcare settings. While current approaches predominantly rely on random masking for…
A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
Yiyuan Yang, Ming Jin, Haomin Wen +9
Diffusion models have been widely used in time series and spatio-temporal data, enhancing generative, inferential, and downstream capabilities. These models are applied across dive…