HIGHLIGHTS
- who: Xiang Yin from the (UNIVERSITY) have published the research work: VAECGAN: a generating framework for long-term prediction in multivariate time series, in the Journal: (JOURNAL)
- what: To improve the accuracy of long-term prediction the authors propose a framework Variational Auto-Encoder Conditional Generative Adversarial Network(VAECGAN). The main contributions of this paper are as follows: A framework VAECGAN is introduced for the long-term prediction. The authors propose a dynamic weights clipping method.
- future: In future work the authors would continue to study the use of the GAN framework to . . .
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