{"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/laplacian","entry":"laplacian","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":10,"n_papers_ran":5,"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":10,"n_samples_ran":5,"n_samples_fingerprinted":1,"n_places":10,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":4,"unverified":5},"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":"2605.10159","paper":"/paper/arxiv-2605-10159","title":"jNO: A JAX Library for Neural Operator and Foundation Model Training","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"FhG-IISB/jNO","path":"jno/fdm.py","file_url":"https://github.com/FhG-IISB/jNO/blob/HEAD/jno/fdm.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"EPL-2.0","inline_ok":false,"code_sha256_prefix":"add2772a15e371e4","mcp_get_code":{"code_sha256":"add2772a15e371e4"}},{"arxiv_id":"2601.04520","paper":"/paper/arxiv-2601-04520","title":"FaceRefiner: High-Fidelity Facial Texture Refinement with Differentiable Rendering-based Style Transfer","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"HarshWinterBytes/FaceRefiner","path":"style_transfer_3d.py","file_url":"https://github.com/HarshWinterBytes/FaceRefiner/blob/HEAD/style_transfer_3d.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"af0d1a80ada41635","mcp_get_code":{"code_sha256":"af0d1a80ada41635"}},{"arxiv_id":"2407.05680","paper":"/paper/fine-grained-multi-view-hand-reconstruction","title":"Fine-Grained Multi-View Hand Reconstruction Using Inverse Rendering","date":"2024-07-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"agnjason/fmhr","path":"models/mesh_sampling.py","file_url":"https://github.com/agnjason/fmhr/blob/HEAD/models/mesh_sampling.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"278d8710708c571f","mcp_get_code":{"code_sha256":"278d8710708c571f"}},{"arxiv_id":"2403.07912","paper":"/paper/handgcat-occlusion-robust-3d-hand-mesh","title":"HandGCAT: Occlusion-Robust 3D Hand Mesh Reconstruction from Monocular Images","date":"2024-02-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"heartstrive/handgcat","path":"common/nets/graph_utils.py","file_url":"https://github.com/heartstrive/handgcat/blob/HEAD/common/nets/graph_utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"47f52b03d406c315","mcp_get_code":{"code_sha256":"47f52b03d406c315"}},{"arxiv_id":"2310.02233","paper":"/paper/generalized-schrodinger-bridge-matching","title":"Generalized Schrödinger Bridge Matching","date":"2023-10-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/generalized-schrodinger-bridge-matching","path":"gsbm/match_loss.py","file_url":"https://github.com/facebookresearch/generalized-schrodinger-bridge-matching/blob/HEAD/gsbm/match_loss.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"d3376279888bc791","mcp_get_code":{"code_sha256":"d3376279888bc791"}},{"arxiv_id":"2310.00697","paper":"/paper/learning-how-to-propagate-messages-in-graph","title":"Learning How to Propagate Messages in Graph Neural Networks","date":"2023-10-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tengxiao1/l2p","path":"full/normalization.py","file_url":"https://github.com/tengxiao1/l2p/blob/HEAD/full/normalization.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9ed3800b90416b36","mcp_get_code":{"code_sha256":"9ed3800b90416b36"}},{"arxiv_id":"2210.13103","paper":"/paper/deep-grey-box-modeling-with-adaptive-data","title":"Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models","date":"2022-10-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"n-takeishi/deepgreybox","path":"reaction-diffusion/make_dataset.py","file_url":"https://github.com/n-takeishi/deepgreybox/blob/HEAD/reaction-diffusion/make_dataset.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b0c79d398c65d6d7","mcp_get_code":{"code_sha256":"b0c79d398c65d6d7"}},{"arxiv_id":"2109.11251","paper":"/paper/trust-region-policy-optimisation-in-multi","title":"Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning","date":"2021-09-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"eduardosebastianrodriguez/phmarl","path":"robotarium/functions.py","file_url":"https://github.com/eduardosebastianrodriguez/phmarl/blob/HEAD/robotarium/functions.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2b9d28f20991d3ec","mcp_get_code":{"code_sha256":"2b9d28f20991d3ec"}},{"arxiv_id":"2005.11041","paper":"/paper/a-survey-of-information-cascade-analysis","title":"A Survey of Information Cascade Analysis: Models, Predictions, and Recent Advances","date":"2020-05-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Xovee/ccgl","path":"src/utils/graphwave/utils/graph_tools.py","file_url":"https://github.com/Xovee/ccgl/blob/HEAD/src/utils/graphwave/utils/graph_tools.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9858df6684d94526","mcp_get_code":{"code_sha256":"9858df6684d94526"}},{"arxiv_id":"1806.02215","paper":"/paper/spectral-inference-networks-unifying-spectral","title":"Spectral Inference Networks: Unifying Deep and Spectral Learning","date":"2018-06-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"deepmind/spectral_inference_networks","path":"spectral_inference_networks/src/spin.py","file_url":"https://github.com/deepmind/spectral_inference_networks/blob/HEAD/spectral_inference_networks/src/spin.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":"6dfa6fe8e9d61fc0","mcp_get_code":{"code_sha256":"6dfa6fe8e9d61fc0"}}]}