{"url":"/dataset/bubbleml","name":"BubbleML","full_name":null,"description_markdown":"A multi-physics dataset of boiling processes.\r\nThis repository includes downloads, visualizations, and sample applications.\r\nThis dataset can be used to train operator networks for phase-change phenomena, act as a ground truth for Physics-Informed Neural Networks, or train computer vision models.","description_withheld":null,"homepage":"https://github.com/HPCForge/BubbleML","introduced_date":"2023-07-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/bubbleml-a-multi-physics-dataset-and","title":"BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning","first_author":"Sheikh Md Shakeel Hassan","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[],"tasks":[{"name":"Physics-informed machine learning","url":"/task/physics-informed-machine-learning","datasets_with_task":"/datasets/task/physics-informed-machine-learning"},{"name":"Operator learning","url":"/task/operator-learning","datasets_with_task":"/datasets/task/operator-learning"}],"languages":[],"variants":["BubbleML"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}