{"url":"/dataset/mujoco","name":"MuJoCo","full_name":null,"description_markdown":"**MuJoCo** (multi-joint dynamics with contact) is a physics engine used to implement environments to benchmark Reinforcement Learning methods.","description_withheld":null,"homepage":"http://www.mujoco.org/","introduced_date":"2012-10-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/mujoco-a-physics-engine-for-model-based","title":"MuJoCo: A physics engine for model-based control","first_author":"Emanuel Todorov","url":null},"license":{"name":"Custom","url":"https://www.roboti.us/license.html"},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Multivariate Time Series Forecasting","url":"/task/multivariate-time-series-forecasting","datasets_with_task":"/datasets/task/multivariate-time-series-forecasting"},{"name":"Multivariate Time Series Imputation","url":"/task/multivariate-time-series-imputation","datasets_with_task":"/datasets/task/multivariate-time-series-imputation"},{"name":"MuJoCo","url":"/task/mujoco","datasets_with_task":"/datasets/task/mujoco"},{"name":"Reinforcement Learning","url":"/task/reinforcement-learning","datasets_with_task":"/datasets/task/reinforcement-learning"}],"languages":[],"variants":["MuJoCo"],"data_loaders":[{"repo":"https://github.com/deepmind/mujoco","url":"https://github.com/deepmind/mujoco","frameworks":[]}],"num_papers_in_archive":1638,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multivariate-time-series-forecasting-on-1","task":"Multivariate Time Series Forecasting","dataset_variant":"MuJoCo","rows":6,"metrics":["MSE (10^-2, 50% missing)"],"first_row_in_archive_order":{"model":"Latent ODE (ODE enc)","paper":"/paper/latent-odes-for-irregularly-sampled-time","metrics":{"MSE (10^-2, 50% missing)":"1.258"},"code_links":[{"title":"YuliaRubanova/latent_ode","url":"https://github.com/YuliaRubanova/latent_ode"},{"title":"patrick-kidger/torchcde","url":"https://github.com/patrick-kidger/torchcde"},{"title":"jacobjinkelly/easy-neural-ode","url":"https://github.com/jacobjinkelly/easy-neural-ode"},{"title":"BorealisAI/continuous-time-flow-process","url":"https://github.com/BorealisAI/continuous-time-flow-process"},{"title":"HerreraKrachTeichmann/ControlledODERNN","url":"https://github.com/HerreraKrachTeichmann/ControlledODERNN"},{"title":"HerreraKrachTeichmann/NJODE","url":"https://github.com/HerreraKrachTeichmann/NJODE"},{"title":"ashysheya/ODE-RNN","url":"https://github.com/ashysheya/ODE-RNN"},{"title":"MeetGandhi/Reconstruction-of-Trajectory-recorded-with-Missing-Markers","url":"https://github.com/MeetGandhi/Reconstruction-of-Trajectory-recorded-with-Missing-Markers"},{"title":"westny/neural-stability","url":"https://github.com/westny/neural-stability"},{"title":"Ldhlwh/Latent-ODE","url":"https://github.com/Ldhlwh/Latent-ODE"},{"title":"gkrudah/ODEnet","url":"https://github.com/gkrudah/ODEnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multivariate-time-series-imputation-on-mujoco","task":"Multivariate Time Series Imputation","dataset_variant":"MuJoCo","rows":6,"metrics":["MSE (10^2, 50% missing)"],"first_row_in_archive_order":{"model":"Latent ODE (ODE enc)","paper":"/paper/latent-odes-for-irregularly-sampled-time","metrics":{"MSE (10^2, 50% missing)":"0.285"},"code_links":[{"title":"YuliaRubanova/latent_ode","url":"https://github.com/YuliaRubanova/latent_ode"},{"title":"patrick-kidger/torchcde","url":"https://github.com/patrick-kidger/torchcde"},{"title":"jacobjinkelly/easy-neural-ode","url":"https://github.com/jacobjinkelly/easy-neural-ode"},{"title":"BorealisAI/continuous-time-flow-process","url":"https://github.com/BorealisAI/continuous-time-flow-process"},{"title":"HerreraKrachTeichmann/ControlledODERNN","url":"https://github.com/HerreraKrachTeichmann/ControlledODERNN"},{"title":"HerreraKrachTeichmann/NJODE","url":"https://github.com/HerreraKrachTeichmann/NJODE"},{"title":"ashysheya/ODE-RNN","url":"https://github.com/ashysheya/ODE-RNN"},{"title":"MeetGandhi/Reconstruction-of-Trajectory-recorded-with-Missing-Markers","url":"https://github.com/MeetGandhi/Reconstruction-of-Trajectory-recorded-with-Missing-Markers"},{"title":"westny/neural-stability","url":"https://github.com/westny/neural-stability"},{"title":"Ldhlwh/Latent-ODE","url":"https://github.com/Ldhlwh/Latent-ODE"},{"title":"gkrudah/ODEnet","url":"https://github.com/gkrudah/ODEnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/latent-odes-for-irregularly-sampled-time","title":"Latent ODEs for Irregularly-Sampled Time Series","date":"2019-07-08","rows_on_this_dataset":4,"code_links":11,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":4,"samples_unverified":4,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/neural-ordinary-differential-equations","title":"Neural Ordinary Differential Equations","date":"2018-06-19","rows_on_this_dataset":4,"code_links":56,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":124,"samples_ran":89,"samples_unverified":35,"pointer_only_for_licence":41,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/recurrent-neural-networks-for-multivariate","title":"Recurrent Neural Networks for Multivariate Time Series with Missing Values","date":"2016-06-06","rows_on_this_dataset":2,"code_links":7,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":1,"samples_unverified":2,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":135,"samples_ran":94,"samples_unverified":41,"pointer_only_for_licence":46,"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."}