551 citations · 847 across the 23 of their papers we have counts for
4 papers · 1 filter
TreeDRNet:A Robust Deep Model for Long Term Time Series Forecasting
Tian Zhou, Jianqing Zhu, Xue Wang +4
Various deep learning models, especially some latest Transformer-based approaches, have greatly improved the state-of-art performance for long-term time series forecasting.However,…
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting
Tian Zhou, Ziqing Ma, Xue wang +5
Recent studies have shown that deep learning models such as RNNs and Transformers have brought significant performance gains for long-term forecasting of time series because they e…
Progressive Backdoor Erasing via connecting Backdoor and Adversarial Attacks
Bingxu Mu, Zhenxing Niu, Le Wang +3
Deep neural networks (DNNs) are known to be vulnerable to both backdoor attacks as well as adversarial attacks. In the literature, these two types of attacks are commonly treated a…
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting
Tian Zhou, Ziqing Ma, Qingsong Wen +3
Although Transformer-based methods have significantly improved state-of-the-art results for long-term series forecasting, they are not only computationally expensive but more impor…