{"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/hessian","entry":"hessian","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":7,"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":7,"n_samples_ran":4,"n_samples_fingerprinted":1,"n_places":10,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":1,"ran":3,"unverified":3},"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":"2603.04523","paper":"/paper/arxiv-2603-04523","title":"Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"Austinrg14/PHL","path":"utils.py","file_url":"https://github.com/Austinrg14/PHL/blob/HEAD/utils.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8704c74ef166273c","mcp_get_code":{"code_sha256":"8704c74ef166273c"}},{"arxiv_id":"2403.19332","paper":"/paper/learning-a-formally-verified-control-barrier","title":"Learning a Formally Verified Control Barrier Function in Stochastic Environment","date":null,"month_inferred_from_arxiv_id":"2024-03","title_source":"archive","repo":"tayalmanan28/Stochastic-NCBF","path":"deep_differential_network/utils.py","file_url":"https://github.com/tayalmanan28/Stochastic-NCBF/blob/HEAD/deep_differential_network/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4878e15d24395c7a","mcp_get_code":{"code_sha256":"4878e15d24395c7a"}},{"arxiv_id":"2403.02467","paper":"/paper/applied-causal-inference-powered-by-ml-and-ai","title":"Applied Causal Inference Powered by ML and AI","date":"2024-03-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"causalaibook/metricsmlnotebooks","path":"T/myxgb.py","file_url":"https://github.com/causalaibook/metricsmlnotebooks/blob/HEAD/T/myxgb.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1de15e976459ba65","mcp_get_code":{"code_sha256":"1de15e976459ba65"}},{"arxiv_id":"2312.04028","paper":"/paper/imface-a-sophisticated-nonlinear-3d-morphable","title":"ImFace++: A Sophisticated Nonlinear 3D Morphable Face Model with Implicit Neural Representations","date":"2023-12-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mingwuzheng/imface","path":"model/diff_opts.py","file_url":"https://github.com/mingwuzheng/imface/blob/HEAD/model/diff_opts.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fd089b9f4b8749ab","mcp_get_code":{"code_sha256":"fd089b9f4b8749ab"}},{"arxiv_id":"2310.04519","paper":"/paper/spade-sparsity-guided-debugging-for-deep","title":"SPADE: Sparsity-Guided Debugging for Deep Neural Networks","date":"2023-10-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ist-daslab/spade","path":"src/BatchSparseGPT.py","file_url":"https://github.com/ist-daslab/spade/blob/HEAD/src/BatchSparseGPT.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4cdb28a41994affd","mcp_get_code":{"code_sha256":"4cdb28a41994affd"}},{"arxiv_id":"2306.08827","paper":"/paper/pinnacle-a-comprehensive-benchmark-of-physics","title":"PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs","date":"2023-06-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"i207m/pinnacle","path":"deepxde/gradients.py","file_url":"https://github.com/i207m/pinnacle/blob/HEAD/deepxde/gradients.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6c180f0e3803ab62","mcp_get_code":{"code_sha256":"6c180f0e3803ab62"}},{"arxiv_id":"2303.14092","paper":"/paper/neuface-realistic-3d-neural-face-rendering","title":"NeuFace: Realistic 3D Neural Face Rendering from Multi-view Images","date":"2023-03-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"aejion/neuface","path":"models/diff_opts.py","file_url":"https://github.com/aejion/neuface/blob/HEAD/models/diff_opts.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fd089b9f4b8749ab","mcp_get_code":{"code_sha256":"fd089b9f4b8749ab"}},{"arxiv_id":"2108.08478","paper":"/paper/learning-anchored-unsigned-distance-functions","title":"Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstruction","date":"2021-08-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhaofang0627/anchorudf","path":"lib/diff_operators.py","file_url":"https://github.com/zhaofang0627/anchorudf/blob/HEAD/lib/diff_operators.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fd089b9f4b8749ab","mcp_get_code":{"code_sha256":"fd089b9f4b8749ab"}},{"arxiv_id":"2006.09661","paper":"/paper/implicit-neural-representations-with-periodic","title":"Implicit Neural Representations with Periodic Activation Functions","date":"2020-06-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vsitzmann/siren","path":"diff_operators.py","file_url":"https://github.com/vsitzmann/siren/blob/HEAD/diff_operators.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fd089b9f4b8749ab","mcp_get_code":{"code_sha256":"fd089b9f4b8749ab"}},{"arxiv_id":"1703.04730","paper":"/paper/understanding-black-box-predictions-via","title":"Understanding Black-box Predictions via Influence Functions","date":"2017-03-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sillwood/voicemos","path":"swag/posteriors/laplace.py","file_url":"https://github.com/sillwood/voicemos/blob/HEAD/swag/posteriors/laplace.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"6ac3796e940e0642","mcp_get_code":{"code_sha256":"6ac3796e940e0642"}}]}