{"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/gaussian-sample","entry":"gaussian_sample","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":9,"n_papers_ran":9,"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":6,"n_samples_ran":6,"n_samples_fingerprinted":5,"n_places":10,"n_places_pointer_only":5,"by_status":{"ran_honours":2,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":1,"ran":2,"unverified":0},"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":"2606.31576","paper":"/paper/arxiv-2606-31576","title":"Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"olewinther/generative-ode-sde","path":"utils.py","file_url":"https://github.com/olewinther/generative-ode-sde/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0070a500ec5d114d","mcp_get_code":{"code_sha256":"0070a500ec5d114d"}},{"arxiv_id":"2307.15073","paper":"/paper/drug-discovery-under-covariate-shift-with","title":"Drug Discovery under Covariate Shift with Domain-Informed Prior Distributions over Functions","date":"2023-07-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"leojklarner/Q-SAVI","path":"qsavi/bayesian_mlps.py","file_url":"https://github.com/leojklarner/Q-SAVI/blob/HEAD/qsavi/bayesian_mlps.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c959ab03acaf0adc","mcp_get_code":{"code_sha256":"c959ab03acaf0adc"}},{"arxiv_id":"2306.10161","paper":"/paper/building-the-bridge-of-schrodinger-a-1","title":"Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark","date":"2023-06-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ngushchin/entropicotbenchmark","path":"benchmark/glow_model.py","file_url":"https://github.com/ngushchin/entropicotbenchmark/blob/HEAD/benchmark/glow_model.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"87324754644a55a3","mcp_get_code":{"code_sha256":"87324754644a55a3"}},{"arxiv_id":"2206.05075","paper":"/paper/diffeomorphic-counterfactuals-with-generative","title":"Diffeomorphic Counterfactuals with Generative Models","date":"2022-06-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"annahdo/counterfactuals","path":"counterfactuals/generative_models/flows/glow.py","file_url":"https://github.com/annahdo/counterfactuals/blob/HEAD/counterfactuals/generative_models/flows/glow.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"87324754644a55a3","mcp_get_code":{"code_sha256":"87324754644a55a3"}},{"arxiv_id":"2105.07239","paper":"/paper/ageflow-conditional-age-progression-and","title":"AgeFlow: Conditional Age Progression and Regression with Normalizing Flows","date":"2021-05-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Hzzone/AgeFlow","path":"flow/models.py","file_url":"https://github.com/Hzzone/AgeFlow/blob/HEAD/flow/models.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"5878daa1dccaec7e","mcp_get_code":{"code_sha256":"5878daa1dccaec7e"}},{"arxiv_id":"1912.01219","paper":"/paper/waveflow-a-compact-flow-based-model-for-raw-1","title":"WaveFlow: A Compact Flow-based Model for Raw Audio","date":"2019-12-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"L0SG/WaveFlow","path":"functions.py","file_url":"https://github.com/L0SG/WaveFlow/blob/HEAD/functions.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"87324754644a55a3","mcp_get_code":{"code_sha256":"87324754644a55a3"}},{"arxiv_id":"1807.03039","paper":"/paper/glow-generative-flow-with-invertible-1x1","title":"Glow: Generative Flow with Invertible 1x1 Convolutions","date":"2018-07-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"rosinality/glow-pytorch","path":"model.py","file_url":"https://github.com/rosinality/glow-pytorch/blob/HEAD/model.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"87324754644a55a3","mcp_get_code":{"code_sha256":"87324754644a55a3"}},{"arxiv_id":"1807.03039","paper":"/paper/glow-generative-flow-with-invertible-1x1","title":"Glow: Generative Flow with Invertible 1x1 Convolutions","date":"2018-07-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"y0ast/Glow-PyTorch","path":"model.py","file_url":"https://github.com/y0ast/Glow-PyTorch/blob/HEAD/model.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"217251eb69420127","mcp_get_code":{"code_sha256":"217251eb69420127"}},{"arxiv_id":"1711.11053","paper":"/paper/a-multi-horizon-quantile-recurrent-forecaster","title":"A Multi-Horizon Quantile Recurrent Forecaster","date":"2017-11-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jingw2/demand_forecast","path":"deepar.py","file_url":"https://github.com/jingw2/demand_forecast/blob/HEAD/deepar.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"5c8cc785cd972816","mcp_get_code":{"code_sha256":"5c8cc785cd972816"}},{"arxiv_id":"Wang_Distribution-Consistent_Modal_Recovering_for_Incomplete_Multimodal_Learning_ICCV_2023_paper","paper":null,"title":"arXiv:Wang_Distribution-Consistent_Modal_Recovering_for_Incomplete_Multimodal_Learning_ICCV_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"mdswyz/DiCMoR","path":"trains/singleTask/model/glow.py","file_url":"https://github.com/mdswyz/DiCMoR/blob/HEAD/trains/singleTask/model/glow.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"87324754644a55a3","mcp_get_code":{"code_sha256":"87324754644a55a3"}}]}