@inproceedings{hou2022multi-granularity,
author = {Hou, Min and Xu, Chang and Li, Zhi and Liu, Yang and Liu, Weiqing and Chen, Enhong and Bian, Jiang},
title = {Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction},
booktitle = {WWW 2022},
year = {2022},
month = {April},
abstract = {Time-series prediction is of high practical value in a wide range of applications such as econometrics and meteorology, where the data are commonly formed by temporal patterns. Most prior works ignore the diversity of dynamic pattern frequency, i.e., different granularities, suffering from insufficient information exploitation. Thus, multi-granularity learning is still under-explored for time-series prediction.},
url = {http://approjects.co.za/?big=en-us/research/publication/multi-granularity-residual-learning-with-confidence-estimation-for-time-series-prediction/},
}