4 papers
AWEMixer: Adaptive Wavelet-Enhanced Mixer Network for Long-Term Time Series Forecasting
Qianyang Li, Xingjun Zhang, Peng Tao +3
Forecasting long-term time series in IoT environments remains a significant challenge due to the non-stationary and multi-scale characteristics of sensor signals. Furthermore, erro…
A Time-Series Foundation Model by Universal Delay Embedding
Zijian Wang, Peng Tao, Jifan Shi +3
This study introduces Universal Delay Embedding (UDE), a pretrained foundation model designed to revolutionize time-series forecasting through principled integration of delay embed…
Delayformer: spatiotemporal transformation for predicting high-dimensional dynamics
Zijian Wang, Peng Tao, Luonan Chen
Predicting time-series is of great importance in various scientific and engineering fields. However, in the context of limited and noisy data, accurately predicting dynamics of all…
Brain-inspired Chaotic Graph Backpropagation for Large-scale Combinatorial Optimization
Peng Tao, Kazuyuki Aihara, Luonan Chen
Graph neural networks (GNNs) with unsupervised learning can solve large-scale combinatorial optimization problems (COPs) with efficient time complexity, making them versatile for v…