{
 "id": "krohnedigital/FuelCast",
 "owner": "krohnedigital",
 "name": "FuelCast",
 "downloads": 340,
 "likes": 5,
 "last_modified": "2026-08-24T12:58:15.000Z",
 "stated_licence": "cc-by-nc-nd-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "tabular-regression",
  "time-series-forecasting"
 ],
 "citation": "@InProceedings{10.1007/978-3-032-15535-1_4,\n    author=\"Viga, Justus\n    and Mueck, Penelope\n    and L{\\\"o}ser, Alexander\n    and Weis, Torben\",\n    editor=\"Lemaire, Vincent\n    and Ifrim, Georgiana\n    and Bagnall, Anthony\n    and Malinowski, Simon\n    and Sch{\\\"a}fer, Patrick\n    and Tavenard, Romain\",\n    title=\"FuelCast: Benchmarking Tabular and Temporal Models for Ship Fuel Consumption\",\n    booktitle=\"Advanced Analytics and Learning on Temporal Data\",\n    year=\"2026\",\n    publisher=\"Springer Nature Switzerland\",\n    address=\"Cham\",\n    pages=\"54--69\",\n    abstract=\"In the shipping industry, fuel consumption and emissions are critical factors due to their significant impact on economic efficiency and environmental sustainability. Accurate prediction of ship fuel consumption is essential for further optimization of maritime operations. However, heterogeneous methodologies and limited high-quality datasets hinder direct comparison of modeling approaches. This paper makes three key contributions: (1) we introduce and release a new dataset (https://huggingface.co/datasets/krohnedigital/FuelCast) comprising operational and environmental data from three ships; (2) we define a standardized benchmark covering tabular regression and time-series regression (3) we investigate the application of in-context learning for ship consumption modeling using the TabPFN foundation model - a first in this domain to our knowledge. Our results demonstrate strong performance across all evaluated",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-nd-4.0) is classified as having use restrictions.",
 "revision": "eb6a6ec011c1c9a2cbce21459e22be4c77ef84dd",
 "stated_evidence": "https://huggingface.co/datasets/krohnedigital/FuelCast/blob/eb6a6ec011c1c9a2cbce21459e22be4c77ef84dd/README.md",
 "file_evidence": "https://huggingface.co/datasets/krohnedigital/FuelCast/tree/eb6a6ec011c1c9a2cbce21459e22be4c77ef84dd",
 "card_nc": false
}