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optimization_manager

Syntologyentry name in harvested coderead from the graph 2026-09-24

optimization_manager appears in the code Syntology harvested for 26 papers, as 9 distinct code bodies found in 26 places (a place is one code body under one paper). At least one of them ran in 21 of the papers; 0 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named optimization_manager do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 5 of the 9 distinct code bodies named optimization_manager; 4 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
4ran
4unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 9 of the 26 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

26 papers shown of 26, newest first; 26 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 1 papers added by Syntology; 1 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
KLIP: localized distribution shift detection via KL-divergence with diffusion priors in Inverse Problems added by Syntology 2026-05 (from id) voilalab/KLIP/song22/losses.py 562a245a3880c52b unverified no licence file found · pointer only
OFTSR: One-Step Flow for Image Super-Resolution with Tunable Fidelity-Realism Trade-offs 12 Dec 2024 yuanzhi-zhu/oftsr/fm/losses.py 4c3fe3149cfaaedc unverified Apache-2.0 (permissive)
Diffusion Twigs with Loop Guidance for Conditional Graph Generation 31 Oct 2024 Aalto-QuML/Diffusion_twigs/losses.py d4922b3c3f09927a unverified MIT (permissive)
Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness 16 Aug 2024 hfmei/idc/IDC-BPDA/score_sde/losses.py 366bb8c7035a2fc8 ran no licence file found · pointer only
Consistency Flow Matching: Defining Straight Flows with Velocity Consistency 2 Jul 2024 yangling0818/consistency_flow_matching/losses.py 366bb8c7035a2fc8 ran MIT (permissive)
Amortizing intractable inference in diffusion models for vision, language, and control 31 May 2024 gfnorg/diffusion-finetuning/diffusion_lm/losses.py 9b714e281bb784b7 ran no licence file found · pointer only
Flow Priors for Linear Inverse Problems via Iterative Corrupted Trajectory Matching 29 May 2024 YasminZhang/ICTM/losses.py 366bb8c7035a2fc8 ran MIT (permissive)
Fast Samplers for Inverse Problems in Iterative Refinement Models 27 May 2024 mandt-lab/c-pigdm/flow/losses.py 366bb8c7035a2fc8 ran no licence file found · pointer only
Bellman Optimal Stepsize Straightening of Flow-Matching Models 27 Dec 2023 nguyenngocbaocmt02/boss/ImageGeneration/losses.py 366bb8c7035a2fc8 ran no licence file found · pointer only
DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification 27 Oct 2023 kangmintong/DiffAttack/DiffAttack_DDPM_Based/score_sde/losses.py 366bb8c7035a2fc8 ran no licence file found · pointer only
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution 25 Oct 2023 louaaron/Score-Entropy-Discrete-Diffusion/losses.py 9b714e281bb784b7 ran MIT (permissive)
Intriguing properties of generative classifiers 28 Sep 2023 SamsungSAILMontreal/ForestDiffusion/STaSy/losses.py 18269deb82a2a3f6 ran no licence file found · pointer only
Variational Bayesian Imaging with an Efficient Surrogate Score-based Prior 5 Sep 2023 berthyf96/score_prior/score_flow/losses.py 53f39e2a10eaea69 ran no licence file found · pointer only
Spontaneous Symmetry Breaking in Generative Diffusion Models 31 May 2023 gabrielraya/symmetry_breaking_diffusion_models/losses.py 366bb8c7035a2fc8 ran MIT (permissive)
MeshDiffusion: Score-based Generative 3D Mesh Modeling 14 Mar 2023 lzzcd001/MeshDiffusion/lib/diffusion/losses.py 366bb8c7035a2fc8 ran MIT (permissive)
GraphGDP: Generative Diffusion Processes for Permutation Invariant Graph Generation 4 Dec 2022 graph-0/graphgdp/losses.py 6d0eb222ef011692 unverified MIT (permissive)
Machine learning emulation of a local-scale UK climate model 29 Nov 2022 henryaddison/score_sde_pytorch/src/ml_downscaling_emulator/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation 9 Oct 2022 sony/fp-diffusion/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
On Investigating the Conservative Property of Score-Based Generative Models 26 Sep 2022 chen-hao-chao/qcsbm/real_world/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
gDDIM: Generalized denoising diffusion implicit models 11 Jun 2022 qsh-zh/gDDIM/blur_jax/losses.py 562a245a3880c52b unverified Apache-2.0 (permissive)
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models 27 May 2022 byeonghu-na/INDM/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
Subspace Diffusion Generative Models 3 May 2022 bjing2016/subspace-diffusion/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
Score-based diffusion models for accelerated MRI 8 Oct 2021 HJ-harry/score-MRI/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation 10 Jun 2021 Kim-Dongjun/Soft-Truncation/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)
Maximum Likelihood Training of Score-Based Diffusion Models 22 Jan 2021 luchengthu/mle_score_ode/losses.py 99dc1b69bbfb52a7 ran · our draft was wrong no licence file found · pointer only
arXiv:Chung_Solving_3D_Inverse_Problems_Using_Pre-Trained_2D_Diffusion_Models_CVPR_2023_paper HJ-harry/DiffusionMBIR/losses.py 366bb8c7035a2fc8 ran Apache-2.0 (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

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