Kangjia Yan — accepted AI-conference papers

2026

Bridging Time and Frequency: A Joint Modeling Framework for Irregular Multivariate Time Series Forecasting

Xiangfei Qiu, Kangjia Yan, Xvyuan Liu, Xingjian Wu, Jilin Hu

ICML 2026poster

Irregular multivariate time series (IMTS) forecasting is challenging due to non-uniform sampling and variable asynchronicity. These irregularities violate the equidistant assumptions of standard models, hindering local temporal modeling and rendering classical frequency-domain methods ineffective fo…

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2026

Invariant Representation Learning for Source-Free Time Series Forecasting with LLM-Centric Proxy Denoising

Kangjia Yan, Chenxi Liu, Hao Miao, Xinle Wu, Yan Zhao, Chenjuan Guo +1

ICML 2026poster

Effective time series forecasting enables various real-world applications, benefiting from the proliferation of mobile devices. However, the volume of time series data may vary significantly across domains due to low sampling rates and data regulations. To maximally create value from sparse data, th…

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