GitHub topics: concept-bottleneck-models
daniuyter/DNCBM-repro
[TMLR, 2025] This is the repository for: Revisiting Discover-then-Name Concept Bottleneck Models: A Reproducibility Study.
Language: Jupyter Notebook - Size: 62.6 MB - Last synced at: 19 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

lmb-freiburg/ucbm
Official code for the paper "Selective Concept Bottleneck Models Without Predefined Concepts" (TMLR 2025)
Language: Python - Size: 2.93 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

Trustworthy-ML-Lab/posthoc-generative-cbm
[CVPR 2025] Concept Bottleneck Autoencoder (CB-AE) -- efficiently transform any pretrained (black-box) image generative model into an interpretable generative concept bottleneck model (CBM) with minimal concept supervision, while preserving image quality
Language: Jupyter Notebook - Size: 3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 7 - Forks: 1

mims-harvard/COMPASS-web
Web Companion for Generalizable AI predicts immunotherapy outcomes across cancers and treatments
Language: Jupyter Notebook - Size: 53 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0

mims-harvard/COMPASS
Generalizable AI predicts immunotherapy outcomes across cancers and treatments
Language: Jupyter Notebook - Size: 676 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 2 - Forks: 0

ssfgunner/IIS
[ICLR 2025 Spotlight] This is the official repository for our paper: ''Enhancing Pre-trained Representation Classifiability can Boost its Interpretability''.
Language: Python - Size: 2.89 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 15 - Forks: 0

CristianoPatricio/CBVLM
Code for the paper "CBVLM: Training-free Explainable Concept-based Large Vision Language Models for Medical Image Classification".
Language: Python - Size: 903 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 7 - Forks: 1

neuroexplicit-saar/Discover-then-Name
Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.
Language: Python - Size: 1.59 MB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 39 - Forks: 2

AIML-MED/AdaCBM
[MICCAI 2024] AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis
Language: Python - Size: 679 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 3 - Forks: 0

djordjepmihajlovic/PyKnot
PyKnot code for Knot Classification & Generation
Language: Python - Size: 37.4 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

i6092467/semi-supervised-multiview-cbm
Concept bottleneck models for multiview data with incomplete concept sets
Language: Python - Size: 100 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 6 - Forks: 0

yewsiang/ConceptBottleneck
Concept Bottleneck Models, ICML 2020
Language: Python - Size: 1.51 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 132 - Forks: 23
