Papers › RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large...
RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data
Chin-Chia Michael Yeh, Yujie Fan, Xin Dai, Uday Singh Saini, Vivian Lai, Prince Osei Aboagye, Junpeng Wang, Huiyuan Chen, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei zhang
Spatial-temporal forecasting systems play a crucial role in addressing numerous real-world challenges. In this paper, we investigate the potential of addressing spatial-temporal forecasting problems using general time series forecasting models, i.e., models that do not leverage the spatial relationships among the nodes. We propose a all-Multi-Layer Perceptron (all-MLP) time series forecasting architecture called RPMixer. The all-MLP architecture was chosen due to its recent success in time series forecasting benchmarks. Furthermore, our method capitalizes on the ensemble-like behavior of deep neural networks, where each individual block within the network behaves like a base learner in an ensemble model, particularly when identity mapping residual connections are incorporated. By integrating random projection layers into our model, we increase the diversity among the blocks' outputs, thereby improving the overall performance of the network. Extensive experiments conducted on the largest spatial-temporal forecasting benchmark datasets demonstrate that the proposed method outperforms alternative methods, including both spatial-temporal graph models and general forecasting models.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Time Series Forecasting | ETTh1 (336) Multivariate | RPMixer | MAE | 0.498 | #65 of 72 | Archive leaderboard | report |
| Time Series Forecasting | ETTh1 (336) Multivariate | RPMixer | MSE | 0.521 | #65 of 72 | Archive leaderboard | report |
| Traffic Prediction | LargeST | RPMixer | CA MAE | 25.07 | #6 of 6 | Archive leaderboard | report |
| Traffic Prediction | LargeST | RPMixer | GBA MAE | 27.77 | #6 of 6 | Archive leaderboard | report |
| Traffic Prediction | LargeST | RPMixer | GLA MAE | 27.87 | #6 of 6 | Archive leaderboard | report |
| Traffic Prediction | LargeST | RPMixer | SD MAE | 25.25 | #6 of 6 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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