{"url":"/dataset/complex-pendulum-motion","name":"Complex pendulum motion","full_name":"Experimental setup for comparing machine learning methods on complex pendulum motion","description_markdown":"Experimental setup (learner code, data generator) for comparing different sequence processors on a dataset generated from motion variables of a pendulum with exponentially-increasing string length.\r\n\r\nThe dataset tests the behaviour of sequence processors on out-of-distribution data because the values of the motion parameters get into new value ranges as the string length increases, although they observe the same underlying laws.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.14899652","introduced_date":"2024-12-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/seqkan-sequence-processing-with-kolmogorov","title":"seqKAN: Sequence processing with Kolmogorov-Arnold Networks","first_author":"Tatiana Boura","url":null},"license":{"name":"CC BY 4.0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["Complex pendulum motion"],"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."}