interpretability-and-explainability

[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

computer-vision deep-learning interpretable-deep-learning concept-bottleneck-models interpretability-and-explainability generative-ai mechanistic-interpretability

Updated Jun 4, 2025
Jupyter Notebook

warisgill / TraceFL

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TraceFL is a novel mechanism for Federated Learning that achieves interpretability by tracking neuron provenance. It identifies clients responsible for global model predictions, achieving 99% accuracy across diverse datasets (e.g., medical imaging) and neural networks (e.g., GPT).

testing debugging machine-learning software-engineering accountability differential-privacy interpretability federated-learning explainable-ai explainability interpretability-and-explainability

Updated Nov 12, 2024
Python

interpretable-ml-class / interpretable-ml-class.github.io

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Explainable AI: From Simple Rules to Complex Generative Models

ai ml interpretability explainable-ai explainable-ml explainability interpretability-and-explainability

Updated Jun 28, 2023
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tail-unica / hopwise

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hopwise: A Python Library for Explainable Recommendation based on Path Reasoning over Knowledge Graphs

recommender-systems link-prediction knowledge-graph-embeddings interpretability-and-explainability path-reasoning

Updated Aug 3, 2025
Python

Skyyyy0920 / SSCBM

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Semi-supervised Concept Bottleneck Models (SSCBM)

concept-bottleneck-models interpretability-and-explainability

Updated Mar 7, 2025
Python

bgreenwell / ebm

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Explainable Boosting Machines

machine-learning ai blackbox interpretability interpretable-ai interpretable-ml explainable-ai explainable-ml xai interpretable interpretable-machine-learning iml glassbox interpretable-models explainable-machine-learning interpretability-and-explainability

Updated Mar 6, 2025
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Imenbaa / BA-LR

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Explainable Speaker Recognition

forensics speaker-recognition resnet34 likelihood-ratio x-vector-pytorch interpretability-and-explainability automatic-voice-comparison forensic-speaker-recognition

Updated Oct 26, 2022
Python

VictorNico / NNs_from_scratch

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Build a Neural net from scratch without keras or pytorch just by using numpy for calculus, pandas for data loading.

neural-network numpy eda pandas mnist oop-principles docstrings simulated-annealing-algorithm interpretability-and-explainability gradiantdescent

Updated Dec 8, 2022
Jupyter Notebook

DimitrisReppas / On_visual_explanation_of_supervised_and_self-supervised_learning

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Visualization methods to interpret CNNs and Vision Transformers, trained in a supervised or self-supervised way. The methods are based on CAM or on the attention mechanism of Transformers. The results are evaluated qualitatively and quantitatively.

deep-neural-networks computer-vision transformers supervised-learning cnns explainable-ai self-supervised-learning interpretability-and-explainability