1 citations · 1 across the 8 of their papers we have counts for
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MLOW: Interpretable Low-Rank Frequency Magnitude Decomposition of Multiple Effects for Time Series Forecasting
Runze Yang, Longbing Cao, Xiaoming Wu +4
Separating multiple effects in time series is fundamental yet challenging for time-series forecasting (TSF). However, existing TSF models cannot effectively learn interpretable mul…
Fourier Basis Mapping: A Time-Frequency Learning Framework for Time Series Forecasting
Runze Yang, Longbing Cao, Xin You +3
The integration of Fourier transform and deep learning opens new avenues for time series forecasting. We reconsider the Fourier transform from a basis functions perspective. Specif…
Modeling enzyme temperature stability from sequence segment perspective
Ziqi Zhang, Shiheng Chen, Runze Yang +10
Developing enzymes with desired thermal properties is crucial for a wide range of industrial and research applications, and determining temperature stability is an essential step i…
Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation
Kun Fang, Qinghua Tao, Mingzhen He +6
Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing the disparities between OoD and In-Dis…