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cs.LG2026
Temporally Unified Adversarial Perturbations for Time Series Forecasting
Ruixian Su, Yukun Bao, Xinze Zhang
While deep learning models have achieved remarkable success in time series forecasting, their vulnerability to adversarial examples remains a critical security concern. However, ex…
cs.LG2024
A Policy Gradient-Based Sequence-to-Sequence Method for Time Series Prediction
Qi Sima, Xinze Zhang, Yukun Bao +2
Sequence-to-sequence architectures built upon recurrent neural networks have become a standard choice for multi-step-ahead time series prediction. In these models, the decoder prod…