{"about":{"site":"https://codewithpapers.app","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.","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"},"url":"/code/symmetric-mse-loss","entry":"symmetric_mse_loss","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":1,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":3,"n_samples_ran":1,"n_samples_fingerprinted":1,"n_places":5,"n_places_pointer_only":0,"by_status":{"ran_honours":1,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":2},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2207.02261","paper":"/paper/openldn-learning-to-discover-novel-classes","title":"OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning","date":"2022-07-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nayeemrizve/OpenLDN","path":"base/losses/losses.py","file_url":"https://github.com/nayeemrizve/OpenLDN/blob/HEAD/base/losses/losses.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"829b0a3dadf8bc76","mcp_get_code":{"code_sha256":"829b0a3dadf8bc76"}},{"arxiv_id":"2006.11280","paper":"/paper/self-pu-self-boosted-and-calibrated-positive","title":"Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training","date":"2020-06-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"TAMU-VITA/Self-PU","path":"mean_teacher/losses.py","file_url":"https://github.com/TAMU-VITA/Self-PU/blob/HEAD/mean_teacher/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d75345cece6fcc81","mcp_get_code":{"code_sha256":"d75345cece6fcc81"}},{"arxiv_id":"2001.06001","paper":"/paper/curriculum-labeling-self-paced-pseudo","title":"Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning","date":"2020-01-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"uvavision/Curriculum-Labeling","path":"utils/losses.py","file_url":"https://github.com/uvavision/Curriculum-Labeling/blob/HEAD/utils/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d75345cece6fcc81","mcp_get_code":{"code_sha256":"d75345cece6fcc81"}},{"arxiv_id":"1912.08265","paper":"/paper/learning-from-synthetic-animals","title":"Learning from Synthetic Animals","date":"2019-12-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"chaneyddtt/UDA-Animal-Pose","path":"pose/losses/jointsmseloss.py","file_url":"https://github.com/chaneyddtt/UDA-Animal-Pose/blob/HEAD/pose/losses/jointsmseloss.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"46dd6446e6572188","mcp_get_code":{"code_sha256":"46dd6446e6572188"}},{"arxiv_id":"1904.04717","paper":"/paper/label-propagation-for-deep-semi-supervised","title":"Label Propagation for Deep Semi-supervised Learning","date":"2019-04-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ahmetius/LP-DeepSSL","path":"mean_teacher/losses.py","file_url":"https://github.com/ahmetius/LP-DeepSSL/blob/HEAD/mean_teacher/losses.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d75345cece6fcc81","mcp_get_code":{"code_sha256":"d75345cece6fcc81"}}]}