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calculate_fid_from_inception_stats
calculate_fid_from_inception_stats appears in the code Syntology harvested for 26 papers, as 6 distinct code bodies found in 27 places (a place is one code body under one paper). At least one of them ran in 26 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 calculate_fid_from_inception_stats 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 6 of the 6 distinct code bodies named calculate_fid_from_inception_stats; 0 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:
Licence is a property of each copy, so it is counted per place: 16 of the 27 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; 27 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 3 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.
| Paper | Date | File | Status Syntology | Licence |
|---|---|---|---|---|
| Elucidating the SNR-t Bias of Diffusion Probabilistic Models added by Syntology | 2026-04 (from id) | AMAP-ML/DCW/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Variational Trajectory Optimization of Anisotropic Diffusion Schedules added by Syntology | 2026-02 (from id) | lizeyu090312/anisotropic-diffusion-paper/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| How I Met Your Bias: Investigating Bias Amplification in Diffusion Models added by Syntology | 2025-12 (from id) | NVlabs/edm/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| arXiv:2507.10072 | 2025-07 (from id) | kunzhan/wpp/EDM-DWT-MM/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation | 11 Jun 2025 | Zyriix/GDD/fid.py 45e941764344e7f3 |
ran · honoured contract | MIT (permissive) |
| Memorization and Regularization in Generative Diffusion Models | 27 Jan 2025 | baptistar/DiffusionModelDynamics/RectangleImages/fid.py 45e941764344e7f3 |
ran · honoured contract | MIT (permissive) |
| Boosting Alignment for Post-Unlearning Text-to-Image Generative Models | 9 Dec 2024 | reds-lab/restricted_gradient_diversity_unlearning/CIFAR/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure | 31 Oct 2024 | Morefre/Understanding-Generalizability-of-Diffusion-Models-Requires-Rethinking-the-Hidden-Gaussian-Structure/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step | 19 Oct 2024 | mingyuanzhou/sid/sid_generate.py 68b5e143931956cf |
ran · honoured contract | Apache-2.0 (permissive) |
| Diffusion Rejection Sampling | 28 May 2024 | aailabkaist/DiffRS/fid_npzs.py 45e941764344e7f3 |
ran · honoured contract | Apache-2.0 (permissive) |
| Learning to Discretize Denoising Diffusion ODEs | 24 May 2024 | vinhsuhi/ld3/compute_fid.py 3c04e2c9c1fea67f |
ran | no licence file found · pointer only |
| Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation | 5 Apr 2024 | mingyuanzhou/SiD/sid_generate.py 68b5e143931956cf |
ran · honoured contract | Apache-2.0 (permissive) |
| Training Unbiased Diffusion Models From Biased Dataset | 2 Mar 2024 | alsdudrla10/TIW-DSM/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion | 1 Oct 2023 | Kim-Dongjun/ctm-cifar10/fid_npzs.py e503281a27d647f2 |
ran | MIT (permissive) |
| Beta Diffusion | 14 Sep 2023 | mingyuanzhou/Beta-Diffusion/image_experiment/fid.py 45e941764344e7f3 |
ran · honoured contract | MIT (permissive) |
| Relay Diffusion: Unifying diffusion process across resolutions for image synthesis | 4 Sep 2023 | THUDM/RelayDiffusion/evaluate.py 45e941764344e7f3 |
ran · honoured contract | Apache-2.0 (permissive) |
| Elucidating the Exposure Bias in Diffusion Models | 29 Aug 2023 | forever208/edm-es/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Fast Training of Diffusion Models with Masked Transformers | 15 Jun 2023 | anima-lab/maskdit/fid.py 45e941764344e7f3 |
ran · honoured contract | MIT (permissive) |
| Fast Diffusion Model | 12 Jun 2023 | sail-sg/fdm/fid.py 45e941764344e7f3 |
ran · honoured contract | Apache-2.0 (permissive) |
| Catch-Up Distillation: You Only Need to Train Once for Accelerating Sampling | 18 May 2023 | shaoshitong/Catch-Up-Distillation/fid.py 2d14332c3e03501e |
ran · honoured contract | no licence file found · pointer only |
| Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models | 25 Apr 2023 | identical code first harvested elsewhere 45e941764344e7f3 |
ran · honoured contract | licence of this copy not recorded |
| A Recipe for Watermarking Diffusion Models | 17 Mar 2023 | yunqing-me/watermarkdm/edm/fid.py 45e941764344e7f3 |
ran · honoured contract | MIT (permissive) |
| Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent | 17 Feb 2023 | identical code first harvested elsewhere 45e941764344e7f3 |
ran · honoured contract | licence of this copy not recorded |
| Minimizing Trajectory Curvature of ODE-based Generative Models | 27 Jan 2023 | sangyun884/fast-ode/fid.py 45e941764344e7f3 |
ran · honoured contract | no licence file found · pointer only |
| Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models | 28 Nov 2022 | identical code first harvested elsewhere 45e941764344e7f3 |
ran · honoured contract | licence of this copy not recorded |
| Elucidating the Design Space of Diffusion-Based Generative Models | 1 Jun 2022 | identical code first harvested elsewhere 45e941764344e7f3 |
ran · honoured contract | licence of this copy not recorded |
| Elucidating the Design Space of Diffusion-Based Generative Models | 1 Jun 2022 | plai-group/vcdm/fid.py 5a0fd9882013c6a5 |
ran · honoured contract | licence not identified · pointer only |
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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