Browse State-of-the-Art › Spatio-Temporal Forecasting
Spatio-Temporal Forecasting
50 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
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
2 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.
Most implemented papers archive 2025-07-28
30 shown of 50 papers with code (87 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.
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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.
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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.
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20 Jan 2019 3 repositories listedThis task is challenging due to the complicated spatiotemporal dependencies among regions.
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20 Jun 2024 2 repositories listed Syntology ran 7 of 7 samples · 0 unverified · 7 pointer-only (licence)We validate ImageFlowNet on three longitudinal medical image datasets depicting progression in geographic atrophy, multiple sclerosis, and glioblastoma, demonstrating its ability to effectively forecast disease…
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30 Aug 2022 2 repositories listedOwing to the continuous and bijective characteristics of NODEs, in addition, we design a one-shot price optimization method given a pre-trained prediction model, which requires only one iteration to find the optimal…
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4 Sep 2020 2 repositories listed Syntology ran 3 of 8 samples · 5 unverifiedAnomaly detection on multivariate time-series is of great importance in both data mining research and industrial applications.
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24 Jul 2017 2 repositories listedThe paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL)and in particular, Recurrent Neural Networks(RNNs).
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1 Apr 2025 1 repository listedAccurate traffic flow forecasting is critical for intelligent transportation systems, yet increasing model complexity in spatiotemporal graph neural networks does not always yield proportional gains.
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4 Mar 2025 1 repository listed Syntology ran 0 of 5 samples · 5 unverifiedData-driven benchmarks have led to significant progress in key scientific modeling domains including weather and structural biology.
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17 Jan 2025 1 repository listedSpatiotemporal forecasting is critical in applications such as traffic prediction, climate modeling, and environmental monitoring.
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18 Dec 2024 1 repository listedOne such example is forecasting the concentration of fine particulate matter (PM2.
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13 Dec 2024 1 repository listed Syntology ran 0 of 5 samples · 5 unverified · 5 pointer-only (licence)Next-generation reservoir computing (NG-RC) has attracted much attention due to its excellent performance in spatio-temporal forecasting of complex systems and its ease of implementation.
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3 Dec 2024 1 repository listedIn this study, we propose a causality-augmented prediction model, called CausalMob, to analyze the causal effects of public events.
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16 Oct 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)The widespread deployment of sensing devices leads to a surge in data for spatio-temporal forecasting applications such as traffic flow, air quality, and wind energy.
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12 Jul 2024 1 repository listedThe primary environmental health threat in the WHO European Region is air pollution, impacting the daily health and well-being of its citizens significantly.
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5 Jul 2024 1 repository listedSpatiotemporal forecasting of traffic flow data represents a typical problem in the field of machine learning, impacting urban traffic management systems.
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19 Jun 2024 1 repository listedMarine fog poses a significant hazard to global shipping, necessitating effective detection and forecasting to reduce economic losses.
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6 Jun 2024 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)Accuracy and timeliness are indeed often conflicting goals in prediction tasks.
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28 May 2024 1 repository listed Syntology ran 10 of 15 samples · 5 unverifiedAdditionally, we incorporate a distribution mapping mechanism to align the data distributions of pre-training and downstream data, facilitating effective knowledge transfer in spatio-temporal forecasting.
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6 May 2024 1 repository listed Syntology ran 7 of 8 samples · 1 unverified · 8 pointer-only (licence)Multi-modality spatio-temporal (MoST) data extends spatio-temporal (ST) data by incorporating multiple modalities, which is prevalent in monitoring systems, encompassing diverse traffic demands and air quality…
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11 Apr 2024 1 repository listed Syntology ran 0 of 1 samples · 1 unverifiedSpatio-temporal forecasting is crucial in real-world dynamic systems, predicting future changes using historical data from diverse locations.
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29 Jan 2024 1 repository listedThe Cy2Mixer is composed of three blocks based on MLPs: A temporal block for capturing temporal properties, a message-passing block for encapsulating spatial information, and a cycle message-passing block for enriching…
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6 Dec 2023 1 repository listedSpatio-temporal forecasting is crucial in various fields and requires a careful balance between identifying subtle patterns and filtering out noise.
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24 Jun 2023 1 repository listedAir quality forecasting has garnered significant attention recently, with data-driven models taking center stage due to advancements in machine learning and deep learning models.
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14 Jun 2023 1 repository listedIn addition, FRIGATE is robust to frugal sensor deployment, changes in road network connectivity, and temporal irregularity in sensing.
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12 Jun 2023 1 repository listed Syntology ran 1 of 6 samples · 5 unverifiedMachine learning approaches for solving partial differential equations require learning mappings between function spaces.
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5 Jun 2023 1 repository listedWe propose two models that are capable of performing multivariate spatio-temporal forecasting while handling missing data naturally without the need for imputation.
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30 May 2023 1 repository listedCurrent works primarily rely on road networks with graph structures and learn representations using graph neural networks (GNNs), but this approach suffers from over-smoothing problem in deep architectures.
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16 May 2023 1 repository listedAlso, by F1-score and probability distribution analysis, we demonstrate that DVGNN better reflects the causal relationship and uncertainty of dynamic graphs.
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21 Feb 2023 1 repository listedTo the best of our knowledge, our Weather2K is the first attempt to tackle weather forecasting task by taking full advantage of the strengths of observation data from ground weather stations.
Syntology lines on 12 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.
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