Demand Forecasting

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 34 papers with code (212 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.

• Graph Neural Network for Traffic Forecasting: A Survey
  27 Jan 2021 4 repositories listed
  In recent years, to model the graph structures in transportation systems as well as contextual information, graph neural networks have been introduced and have achieved state-of-the-art performance in a series of…
• Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset and Benchmarks
  13 Nov 2024 3 repositories listed
  Graph Neural Networks (GNNs) have recently gained traction in transportation, bioinformatics, language and image processing, but research on their application to supply chain management remains limited.
• Demand Forecasting from Spatiotemporal Data with Graph Networks and Temporal-Guided Embedding
  26 May 2019 3 repositories listed
  TGNet learns an autoregressive model, conditioned on temporal contexts of forecasting targets from temporal-guided embedding.
• Spatiotemporal Multi-Graph Convolution Networkfor Ride-hailing Demand Forecasting
  20 Jan 2019 3 repositories listed
  This task is challenging due to the complicated spatiotemporal dependencies among regions.
• High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
  7 Oct 2019 2 repositories listed Syntology ran 0 of 12 samples · 12 unverified
  Predicting the dependencies between observations from multiple time series is critical for applications such as anomaly detection, financial risk management, causal analysis, or demand forecasting.
• ADFormer: Aggregation Differential Transformer for Passenger Demand Forecasting
  3 Jun 2025 1 repository listed
  Effectively integrating these high-level correlations with the original correlations is crucial.
• FreshRetailNet-50K: A Stockout-Annotated Censored Demand Dataset for Latent Demand Recovery and Forecasting in Fresh Retail
  22 May 2025 1 repository listed
  The hourly stock status records unique to this dataset, combined with rich contextual covariates, including promotional discounts, precipitation, and temporal features, enable innovative research beyond existing…
• SPDNet: Seasonal-Periodic Decomposition Network for Advanced Residential Demand Forecasting
  28 Mar 2025 1 repository listed
  However, real-world residential electricity demand data often exhibit intricate temporal variability, including multiple seasonalities, periodicities, and abrupt fluctuations, which pose significant challenges for…
• Forecasting time series with constraints
  14 Feb 2025 1 repository listed
  Time series forecasting presents unique challenges that limit the effectiveness of traditional machine learning algorithms.
• Probabilistic energy forecasting through quantile regression in reproducing kernel Hilbert spaces
  8 Aug 2024 1 repository listed
  Accurate energy demand forecasting is crucial for sustainable and resilient energy development.
• Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity
  2 Jul 2024 1 repository listed
  Recent works, however, do not address two important challenges that are typically observed in many demand forecasting applications at large companies.
• Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking
  17 Jun 2024 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  We benchmark a range of models on this dataset, evaluating their performance in standard scenarios, in predictions focused on lower value ranges, and in the presence of structural breaks, providing new insights for…
• Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly
  22 May 2024 1 repository listed
  However, reliable time series sales forecasting for e-commerce is difficult, especially during periods with many anomalies, as can often happen during pandemics, abnormal weather, or sports events.
• Any-Quantile Probabilistic Forecasting of Short-Term Electricity Demand
  26 Apr 2024 1 repository listed
  We show that our general approach can be seamlessly applied to two distinct neural architectures leading to the state-of-the-art distributional forecasting results in the context of short-term electricity demand…
• Scalable Spatiotemporal Prediction with Bayesian Neural Fields
  12 Mar 2024 1 repository listed Syntology ran 7 of 7 samples · 0 unverified
  Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-demand forecasting.
• Global Rewards in Multi-Agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
  14 Dec 2023 1 repository listed
  We study vehicle dispatching in autonomous mobility on demand (AMoD) systems, where a central operator assigns vehicles to customer requests or rejects these with the aim of maximizing its total profit.
• Adaptive Dependency Learning Graph Neural Networks
  6 Dec 2023 1 repository listed
  In this paper, we propose a hybrid approach combining neural networks and statistical structure learning models to self-learn the dependencies and construct a dynamically changing dependency graph from multivariate data…
• Supply Chain Forecasting in a Fast-Moving Global Economy: Review, Limits and Future Directions
  1 Sep 2023 1 repository listed
  The supply chain demand forecasting field has evolved to meet customer demand, preventing lost sales opportunities, and reducing maintenance costs.
• PM-Gati Shakti: Advancing India's Energy Future through Demand Forecasting -- A Case Study
  30 Jul 2023 1 repository listed
  As Electrical Forecasting includes many factors which cannot be detected by the models out there, We use Classical Forecasting Techniques to extract the seasonal patterns from the daily data of Maximum Demand for the…
• Semi-decentralized Inference in Heterogeneous Graph Neural Networks for Traffic Demand Forecasting: An Edge-Computing Approach
  28 Feb 2023 1 repository listed
  This approach minimizes inter-cloudlet communication thereby alleviating the communication overhead of the decentralized approach while promoting scalability due to cloudlet-level decentralization.
• Forecasting railway ticket demand with search query open data
  23 Nov 2022 1 repository listed
  A time series of web search queries is used as a predictor, and demand time series for train tickets is used as a target variable.
• Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction
  30 Jun 2022 1 repository listed
  Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society.
• A deep inverse reinforcement learning approach to route choice modeling with context-dependent rewards
  18 Jun 2022 1 repository listed
  Route choice modeling is a fundamental task in transportation planning and demand forecasting.
• Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand
  21 Jun 2021 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  To meet this requirement, accurate forecasting of the charging demand is vital.
• Policy choices can help keep 4G and 5G universal broadband affordable
  19 Jan 2021 1 repository listed
  The cost of meeting a minimum 10 Mbps per user is estimated at USD 1.
• ProVe -- Self-supervised pipeline for automated product replacement and cold-starting based on neural language models
  26 Jun 2020 1 repository listed
  Moreover, we will propose a solution for managing products that were newly introduced in a retailer's portfolio with almost no transactional history.
• Additive stacking for disaggregate electricity demand forecasting
  20 May 2020 1 repository listed
  We focus on forecasting demand at the individual household level, which is more challenging than forecasting aggregate demand, due to the lower signal-to-noise ratio and to the heterogeneity of consumption patterns…
• Intermittent Demand Forecasting with Deep Renewal Processes
  23 Nov 2019 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  Intermittent demand, where demand occurrences appear sporadically in time, is a common and challenging problem in forecasting.
• Spatiotemporal Multi-Graph Convolution Network for Ride-hailing Demand Forecasting
  17 Jul 2019 1 repository listed
  This task is challenging due to the complicated spatiotemporal dependencies among regions.
• STG2Seq: Spatial-temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting
  24 May 2019 1 repository listed
  Multi-step passenger demand forecasting is a crucial task in on-demand vehicle sharing services.

Syntology lines on 5 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.