{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/friction/papers/5","list_of":"/task/friction","task":"Friction","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":5,"pages_in_order":5,"rows_per_page":100,"rows":[401,418],"of":418,"counts":{"archive_papers_tagged":418,"with_a_code_link":62,"where_syntology_ran_a_sample":14,"not_listed_spam_title":0,"listed":418,"listed_where_code_ran":14,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":12,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":12,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/friction","prev":"/task/friction/papers/4","next":null,"papers":[{"url":null,"slug":"the-impact-of-hydrodynamic-interactions-on","title":"The impact of hydrodynamic interactions on protein folding rates depends on temperature","date":"2017-12-12","arxiv_id":"1712.03926","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-model-identification-via-physics-engines","title":"Fast Model Identification via Physics Engines for Data-Efficient Policy Search","date":"2017-10-24","arxiv_id":"1710.08893","repositories_listed":0,"syntology":null},{"url":null,"slug":"infant-footprint-recognition","title":"Infant Footprint Recognition","date":"2017-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"road-friction-estimation-for-connected","title":"Road Friction Estimation for Connected Vehicles using Supervised Machine Learning","date":"2017-09-15","arxiv_id":"1709.05379","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-conservation-law-method-in-optimization","title":"A Conservation Law Method in Optimization","date":"2017-08-27","arxiv_id":"1708.08035","repositories_listed":0,"syntology":null},{"url":null,"slug":"material-recognition-cnns-and-hierarchical","title":"Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain","date":"2017-06-27","arxiv_id":"1706.08685","repositories_listed":0,"syntology":null},{"url":null,"slug":"highly-curved-image-sensors-a-practical","title":"Highly curved image sensors: a practical approach for improved optical performance","date":"2017-06-20","arxiv_id":"1706.07041","repositories_listed":0,"syntology":null},{"url":null,"slug":"unlocking-the-potential-of-simulators-design","title":"Unlocking the Potential of Simulators: Design with RL in Mind","date":"2017-06-08","arxiv_id":"1706.02501","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-measurement-of-pre-aspiration","title":"Automatic Measurement of Pre-aspiration","date":"2017-04-05","arxiv_id":"1704.01653","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-theoretic-model-identification","title":"Information-theoretic Model Identification and Policy Search using Physics Engines with Application to Robotic Manipulation","date":"2017-03-22","arxiv_id":"1703.07822","repositories_listed":0,"syntology":null},{"url":null,"slug":"filament-turnover-is-essential-for-continuous","title":"Filament turnover is essential for continuous long range contractile flow in a model actomyosin cortex","date":"2016-12-22","arxiv_id":"1612.07430","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-perform-physics-experiments-via","title":"Learning to Perform Physics Experiments via Deep Reinforcement Learning","date":"2016-11-06","arxiv_id":"1611.01843","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-from-simulation-to-real-world","title":"Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model","date":"2016-10-11","arxiv_id":"1610.03518","repositories_listed":0,"syntology":null},{"url":null,"slug":"force-from-motion-decoding-physical-sensation","title":"Force From Motion: Decoding Physical Sensation in a First Person Video","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"friction-from-reflectance-deep-reflectance","title":"Friction from Reflectance: Deep Reflectance Codes for Predicting Physical Surface Properties from One-Shot In-Field Reflectance","date":"2016-03-25","arxiv_id":"1603.07998","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-universal-tradeoff-between-power-precision","title":"A universal tradeoff between power, precision and speed in physical communication","date":"2016-03-24","arxiv_id":"1603.07758","repositories_listed":0,"syntology":null},{"url":null,"slug":"galileo-perceiving-physical-object-properties","title":"Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning","date":"2015-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tissue-fusion-over-non-adhering-surfaces","title":"Tissue fusion over non-adhering surfaces","date":"2015-08-11","arxiv_id":"1508.02582","repositories_listed":0,"syntology":null}],"record_sha256":"f47ee967298ad98b5a64088299f2aa01db6d114b04834be2b99f1c6c3d0c7312","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}