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BayesCap

imported

software/bayescap

(ECCV 2022) BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

Machine-generated from the listed sources and not yet reviewed by a human.

BayesCap project image
GitHub preview card for ExplainableML/BayesCap. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
ExplainableML
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
calibration · computer-vision · deblurring · deep-learning · depth-estimation · gans · image-translation · inpainting · machine-learning · medical-imaging · uncertainty · uncertainty-calibration · uncertainty-estimation · uncertainty-quantification · uncertainty-visualisation
Regulatory
unknown
built by · 2

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

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    (ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models

  • quickNAT_pytorchcomputer-vision · medical-imaging · uncertainty

    PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

  • deepinvdeblurring · medical-imaging

    DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning

  • MT-ENetuncertainty-estimation · uncertainty-quantification

    Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022

sources
  1. api.github.com/repos/ExplainableML/BayesCap
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2022-12-14, 52 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/53.json→ .entries["bayescap"]

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