Back to papers
A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis
Summary: MSD-Mixer: an MLP‑Mixer that explicitly decomposes uni-/multivariate time series using multi-scale temporal patching and MLPs to model intra/inter-patch dynamics and channel correlations. New loss constrains residual mean and autocorrelation for decomposition completeness; achieves consistent, efficient SOTA across five time-series tasks.
(summarized by gpt-5-mini on Feb 09 2026)
- Paper ID
- 13412
- Venue
- VLDB
- Year
- 2024
- Pagerank
- 4.4520434e-05
- Overall Rank
- 8,740 | 39.26%
- DOI
-
10.14778/3654621.3654637
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 11 of 11 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 1,253 |
Anomaly Detection in Time Series: A Comprehensive Evaluation |
2022 |
VLDB |
0.00013019488 |
| 2,052 |
TraClass: Trajectory Classification Using Hierarchical Region-Based and Trajectory-Based Clustering |
2008 |
VLDB |
9.6854498e-05 |
| 2,282 |
Mind the Gap: An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series |
2020 |
VLDB |
9.1173974e-05 |
| 2,381 |
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection |
2022 |
VLDB |
8.9241557e-05 |
| 3,413 |
MDTP: A Multi-source Deep Traffic Prediction Framework over Spatio-Temporal Trajectory Data |
2021 |
VLDB |
7.1184306e-05 |
| 3,470 |
DeepTRANS: A Deep Learning System for Public Bus Travel Time Estimation using Traffic Forecasting |
2020 |
VLDB |
7.0628698e-05 |
| 3,946 |
Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection |
2022 |
VLDB |
6.6036232e-05 |
| 4,331 |
Missing Value Imputation on Multidimensional Time Series |
2021 |
VLDB |
6.2744869e-05 |
| 4,892 |
Forecasting Big Time Series: Old and New |
2018 |
VLDB |
5.8474831e-05 |
| 5,265 |
Probabilistic Demand Forecasting at Scale |
2017 |
VLDB |
5.5950627e-05 |
| 5,899 |
METRO: A Generic Graph Neural Network Framework for Multivariate Time Series Forecasting |
2022 |
VLDB |
5.2806419e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 2,429 |
Optimal Multi-scale Patterns in Time Series Streams |
2006 |
SIGMOD |
8.8285306e-05 |
| 8,279 |
OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And Forecasting |
2023 |
VLDB |
4.5392079e-05 |
| 6,849 |
Time2Feat: Learning Interpretable Representations for Multivariate Time Series Clustering |
2023 |
VLDB |
4.903714e-05 |
| 10,746 |
Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods |
2025 |
VLDB |
4.1905499e-05 |
| 7,274 |
Interpretable Clustering of Multivariate Time Series with Time2Feat |
2023 |
VLDB |
4.7748043e-05 |
| 5,479 |
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles |
2022 |
VLDB |
5.4849266e-05 |
| 13,170 |
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation Learning |
2024 |
VLDB |
- |
| 4,331 |
Missing Value Imputation on Multidimensional Time Series |
2021 |
VLDB |
6.2744869e-05 |
| 6,205 |
OnlineSTL: Scaling Time Series Decomposition by 100x |
2022 |
VLDB |
5.1541127e-05 |
| 10,880 |
MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection |
2025 |
VLDB |
4.1905499e-05 |