Multivariate Time Series Forecasting

Benchmarks archive 2025-07-28

17 leaderboard tables shown for this task, 17 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 17 until expanded.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

18 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 153 papers with code (245 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Neural Ordinary Differential Equations
  19 Jun 2018 56 repositories listed Syntology ran 89 of 124 samples · 35 unverified · 41 pointer-only (licence)
  Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network.
• Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
  21 Mar 2017 21 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.
• Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
  6 Jul 2017 19 repositories listed Syntology ran 17 of 35 samples · 18 unverified · 15 pointer-only (licence)
  Spatiotemporal forecasting has various applications in neuroscience, climate and transportation domain.
• DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
  13 Apr 2017 19 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Probabilistic forecasting, i.
• Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
  14 Dec 2020 14 repositories listed Syntology ran 62 of 76 samples · 14 unverified · 13 pointer-only (licence)
  Many real-world applications require the prediction of long sequence time-series, such as electricity consumption planning.
• Latent ODEs for Irregularly-Sampled Time Series
  8 Jul 2019 11 repositories listed Syntology ran 4 of 8 samples · 4 unverified · 3 pointer-only (licence)
  Time series with non-uniform intervals occur in many applications, and are difficult to model using standard recurrent neural networks (RNNs).
• AA-Forecast: Anomaly-Aware Forecast for Extreme Events
  21 Aug 2022 9 repositories listed
  Moreover, the framework employs a dynamic uncertainty optimization algorithm that reduces the uncertainty of forecasts in an online manner.
• A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
  27 Nov 2022 8 repositories listed Syntology ran 7 of 30 samples · 23 unverified
  Our channel-independent patch time series Transformer (PatchTST) can improve the long-term forecasting accuracy significantly when compared with that of SOTA Transformer-based models.
• Recurrent Neural Networks for Multivariate Time Series with Missing Values
  6 Jun 2016 7 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 2 pointer-only (licence)
  Multivariate time series data in practical applications, such as health care, geoscience, and biology, are characterized by a variety of missing values.
• Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis
  9 Oct 2023 5 repositories listed Syntology ran 5 of 12 samples · 7 unverified · 4 pointer-only (licence)
  Multivariate Time Series (MTS) analysis is crucial to understanding and managing complex systems, such as traffic and energy systems, and a variety of approaches to MTS forecasting have been proposed recently.
• Probabilistic Forecasting with Temporal Convolutional Neural Network
  11 Jun 2019 5 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  We present a probabilistic forecasting framework based on convolutional neural network for multiple related time series forecasting.
• BRITS: Bidirectional Recurrent Imputation for Time Series
  27 May 2018 5 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  It is ubiquitous that time series contains many missing values.
• Predictive Business Process Monitoring with LSTM Neural Networks
  7 Dec 2016 5 repositories listed
  First, we show that LSTMs outperform existing techniques to predict the next event of a running case and its timestamp.
• Temporal Pattern Attention for Multivariate Time Series Forecasting
  12 Sep 2018 4 repositories listed
  To obtain accurate prediction, it is crucial to model long-term dependency in time series data, which can be achieved to some good extent by recurrent neural network (RNN) with attention mechanism.
• Efficient Multivariate Time Series Forecasting via Calibrated Language Models with Privileged Knowledge Distillation
  4 May 2025 3 repositories listed Syntology ran 5 of 7 samples · 2 unverified
  To address this problem, we introduce TimeKD, an efficient MTSF framework that leverages the calibrated language models and privileged knowledge distillation.
• TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
  3 Jun 2024 3 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  As another key design, to reduce the computational costs from time series with their length textual prompts, we design an effective prompt to encourage the most essential temporal information to be encapsulated in the…
• TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
  29 Mar 2024 3 repositories listed Syntology ran 4 of 4 samples · 0 unverified
  Next, we employ TFB to perform a thorough evaluation of 21 Univariate Time Series Forecasting (UTSF) methods on 8, 068 univariate time series and 14 Multivariate Time Series Forecasting (MTSF) methods on 25 datasets.
• Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting
  13 Mar 2021 3 repositories listed Syntology ran 2 of 13 samples · 11 unverified · 2 pointer-only (licence)
  In this paper, we propose Spectral Temporal Graph Neural Network (StemGNN) to further improve the accuracy of multivariate time-series forecasting.
• Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting
  6 Jul 2020 3 repositories listed Syntology ran 5 of 7 samples · 2 unverified · 1 pointer-only (licence)
  We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.
• Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
  24 May 2020 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)
  Modeling multivariate time series has long been a subject that has attracted researchers from a diverse range of fields including economics, finance, and traffic.
• GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series
  29 May 2019 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Modeling real-world multidimensional time series can be particularly challenging when these are sporadically observed (i.
• Structured Inference Networks for Nonlinear State Space Models
  30 Sep 2016 3 repositories listed Syntology ran 2 of 13 samples · 11 unverified
  We introduce a unified algorithm to efficiently learn a broad class of linear and non-linear state space models, including variants where the emission and transition distributions are modeled by deep neural networks.
• DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting
  14 Dec 2024 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  First, we design a Temporal Clustering Module (TCM) that clusters time series into fine-grained distributions to handle heterogeneous temporal patterns.
• CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning
  12 Mar 2024 2 repositories listed Syntology ran 3 of 5 samples · 2 unverified
  Unlike existing methods that focus on training models from a single modal of time series input, large language models (LLMs) based MTSF methods with cross-modal text and time series input have recently shown great…
• Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators
  31 Jan 2024 2 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 11 pointer-only (licence)
  Recently, channel-independent methods have achieved state-of-the-art performance in multivariate time series (MTS) forecasting.
• Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach
  4 Dec 2023 2 repositories listed
  To address this challenge, we present the Super-Multivariate Urban Mobility Transformer (SUMformer), which utilizes a specially designed attention mechanism to calculate temporal and cross-variable correlations and…
• MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation
  25 Sep 2023 2 repositories listed
  Urban time series data forecasting featuring significant contributions to sustainable development is widely studied as an essential task of the smart city.
• Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting
  2 Feb 2023 2 repositories listed
  Utilizing DSW embedding and TSA layer, Crossformer establishes a Hierarchical Encoder-Decoder (HED) to use the information at different scales for the final forecasting.
• StockEmotions: Discover Investor Emotions for Financial Sentiment Analysis and Multivariate Time Series
  23 Jan 2023 2 repositories listed
  There has been growing interest in applying NLP techniques in the financial domain, however, resources are extremely limited.
• Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting
  10 Aug 2022 2 repositories listed
  These results suggest that we can design efficient and effective models as long as they solve the indistinguishability of samples, without being limited to STGNNs.

Syntology lines on 22 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.