{"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/bn","entry":"bn","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":19,"n_papers_ran":13,"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":11,"n_samples_ran":5,"n_samples_fingerprinted":2,"n_places":20,"n_places_pointer_only":8,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":2,"ran_fixture":0,"ran":3,"unverified":6},"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":"2509.11724","paper":"/paper/arxiv-2509-11724","title":"DRAG: Data Reconstruction Attack using Guided Diffusion","date":null,"month_inferred_from_arxiv_id":"2025-09","title_source":"syntology","repo":"ntuaislab/DRAG","path":"models/likelihood_maximization.py","file_url":"https://github.com/ntuaislab/DRAG/blob/HEAD/models/likelihood_maximization.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"2407.14816","paper":"/paper/blind-image-deconvolution-by-generative-based","title":"Blind Image Deconvolution by Generative-based Kernel Prior and Initializer via Latent Encoding","date":"2024-07-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jtaoz/gkpile-deconvolution","path":"networks/common.py","file_url":"https://github.com/jtaoz/gkpile-deconvolution/blob/HEAD/networks/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"BSD-2-Clause","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"2405.16749","paper":"/paper/dmplug-a-plug-in-method-for-solving-inverse","title":"DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models","date":"2024-05-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"csdwren/SelfDeblur","path":"models/common.py","file_url":"https://github.com/csdwren/SelfDeblur/blob/HEAD/models/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"2404.15620","paper":"/paper/a-dynamic-kernel-prior-model-for-unsupervised","title":"A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution","date":"2024-04-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"XYLGroup/DKP","path":"DIPDKP/DIPDKP/model/common.py","file_url":"https://github.com/XYLGroup/DKP/blob/HEAD/DIPDKP/DIPDKP/model/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"2206.09104","paper":"/paper/score-guided-intermediate-layer-optimization","title":"Score-Guided Intermediate Layer Optimization: Fast Langevin Mixing for Inverse Problems","date":"2022-06-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"giannisdaras/ilo","path":"ilo_biggan.py","file_url":"https://github.com/giannisdaras/ilo/blob/HEAD/ilo_biggan.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"681a8a8bb1689e7a","mcp_get_code":{"code_sha256":"681a8a8bb1689e7a"}},{"arxiv_id":"2204.04950","paper":"/paper/commonality-in-natural-images-rescues-gans","title":"Commonality in Natural Images Rescues GANs: Pretraining GANs with Generic and Privacy-free Synthetic Data","date":"2022-04-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"FriedRonaldo/Primitives-PS","path":"cifar/diffAug-cifar-posttrain/BigGAN.py","file_url":"https://github.com/FriedRonaldo/Primitives-PS/blob/HEAD/cifar/diffAug-cifar-posttrain/BigGAN.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e9d1f7dec1c996a1","mcp_get_code":{"code_sha256":"e9d1f7dec1c996a1"}},{"arxiv_id":"2103.17022","paper":"/paper/layout-guided-novel-view-synthesis-from-a","title":"Layout-Guided Novel View Synthesis from a Single Indoor Panorama","date":"2021-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/synsin","path":"models/z_buffermodel.py","file_url":"https://github.com/facebookresearch/synsin/blob/HEAD/models/z_buffermodel.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"e499647e5bba64ae","mcp_get_code":{"code_sha256":"e499647e5bba64ae"}},{"arxiv_id":"2102.06696","paper":"/paper/efficient-conditional-gan-transfer-with","title":"Efficient Conditional GAN Transfer with Knowledge Propagation across Classes","date":"2021-02-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mshahbazi72/cGANTransfer","path":"BigGAN.py","file_url":"https://github.com/mshahbazi72/cGANTransfer/blob/HEAD/BigGAN.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1c85899609ec850d","mcp_get_code":{"code_sha256":"1c85899609ec850d"}},{"arxiv_id":"1903.11269","paper":"/paper/css10-a-collection-of-single-speaker-speech","title":"CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages","date":"2019-03-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Kyubyong/css10","path":"tacotron/modules.py","file_url":"https://github.com/Kyubyong/css10/blob/HEAD/tacotron/modules.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"21f623855d3d8bb9","mcp_get_code":{"code_sha256":"21f623855d3d8bb9"}},{"arxiv_id":"1901.11365","paper":"/paper/noise2self-blind-denoising-by-self","title":"Noise2Self: Blind Denoising by Self-Supervision","date":"2019-01-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mozanunal/SparseCT","path":"sparse_ct/model/common.py","file_url":"https://github.com/mozanunal/SparseCT/blob/HEAD/sparse_ct/model/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"1805.05553","paper":"/paper/on-learning-associations-of-faces-and-voices","title":"On Learning Associations of Faces and Voices","date":"2018-05-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"changil/facevoice","path":"facevoice.py","file_url":"https://github.com/changil/facevoice/blob/HEAD/facevoice.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"292d30c5795a85f6","mcp_get_code":{"code_sha256":"292d30c5795a85f6"}},{"arxiv_id":"1804.04391","paper":"/paper/mggan-solving-mode-collapse-using-manifold","title":"MGGAN: Solving Mode Collapse using Manifold Guided Training","date":"2018-04-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"QuickSolverKyle/Tensorflow-MyGANs","path":"ops.py","file_url":"https://github.com/QuickSolverKyle/Tensorflow-MyGANs/blob/HEAD/ops.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"0ebe72a4409e7f3b","mcp_get_code":{"code_sha256":"0ebe72a4409e7f3b"}},{"arxiv_id":"1711.10925","paper":"/paper/deep-image-prior","title":"Deep Image Prior","date":"2017-11-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dniku/perceptual-gradient-networks","path":"archs/deep_image_prior/common.py","file_url":"https://github.com/dniku/perceptual-gradient-networks/blob/HEAD/archs/deep_image_prior/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MPL-2.0","inline_ok":false,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"1703.10135","paper":"/paper/tacotron-towards-end-to-end-speech-synthesis","title":"Tacotron: Towards End-to-End Speech Synthesis","date":"2017-03-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Kyubyong/tacotron","path":"modules.py","file_url":"https://github.com/Kyubyong/tacotron/blob/HEAD/modules.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"21f623855d3d8bb9","mcp_get_code":{"code_sha256":"21f623855d3d8bb9"}},{"arxiv_id":"1611.09326","paper":"/paper/the-one-hundred-layers-tiramisu-fully","title":"The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation","date":"2016-11-28","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ankit-vaghela30/Cilia-Segmentation","path":"hastings/tiramisu_model.py","file_url":"https://github.com/ankit-vaghela30/Cilia-Segmentation/blob/HEAD/hastings/tiramisu_model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"011e9d1f4a18f0c1","mcp_get_code":{"code_sha256":"011e9d1f4a18f0c1"}},{"arxiv_id":"1512.03385","paper":"/paper/deep-residual-learning-for-image-recognition","title":"Deep Residual Learning for Image Recognition","date":"2015-12-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters","path":"modified_resnet.py","file_url":"https://github.com/xinkuansong/modified-resnet-acc-0.9638-10.7M-parameters/blob/HEAD/modified_resnet.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3be20b1c2fd39dff","mcp_get_code":{"code_sha256":"3be20b1c2fd39dff"}},{"arxiv_id":"1512.03385","paper":"/paper/deep-residual-learning-for-image-recognition","title":"Deep Residual Learning for Image Recognition","date":"2015-12-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ry/tensorflow-resnet","path":"resnet.py","file_url":"https://github.com/ry/tensorflow-resnet/blob/HEAD/resnet.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a119c928e7d50ee1","mcp_get_code":{"code_sha256":"a119c928e7d50ee1"}},{"arxiv_id":"Zang_IntraTomo_Self-Supervised_Learning-Based_Tomography_via_Sinogram_Synthesis_and_Prediction_ICCV_2021_paper","paper":null,"title":"arXiv:Zang_IntraTomo_Self-Supervised_Learning-Based_Tomography_via_Sinogram_Synthesis_and_Prediction_ICCV_2021_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"matheusgadelha/ShapeRecDeepPrior","path":"models/common.py","file_url":"https://github.com/matheusgadelha/ShapeRecDeepPrior/blob/HEAD/models/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"Li_Self-Supervised_Blind_Motion_Deblurring_With_Deep_Expectation_Maximization_CVPR_2023_paper","paper":null,"title":"arXiv:Li_Self-Supervised_Blind_Motion_Deblurring_With_Deep_Expectation_Maximization_CVPR_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"Chilie/Deblur_MCEM","path":"networks/common.py","file_url":"https://github.com/Chilie/Deblur_MCEM/blob/HEAD/networks/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}},{"arxiv_id":"Li_Deep_Random_Projector_Accelerated_Deep_Image_Prior_CVPR_2023_paper","paper":null,"title":"arXiv:Li_Deep_Random_Projector_Accelerated_Deep_Image_Prior_CVPR_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"sun-umn/Deep-Random-Projector","path":"1_Denoising/models/common.py","file_url":"https://github.com/sun-umn/Deep-Random-Projector/blob/HEAD/1_Denoising/models/common.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cd7e7024386fb823","mcp_get_code":{"code_sha256":"cd7e7024386fb823"}}]}