MICCAI 2022 (Oral): Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis
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Apr 29, 2023 - Python
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interpretability-and-explainability
Here are 12 public repositories matching this topic...
Discover and Cure: Concept-aware Mitigation of Spurious Correlation (ICML 2023)
pytorch data-augmentation generalization interpretability-and-explainability stable-diffusion icml-2023 spurious-correlation
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Apr 14, 2024 - Python
[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"
graph-neural-networks rationalization molecular-property-prediction interpretability-and-explainability polymer-property-prediction
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Mar 27, 2025 - Python
Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks."
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Apr 2, 2022 - Python
[ICCV 2023] Learning Support and Trivial Prototypes for Interpretable Image Classification
image-recognition fine-grained-classification interpretable-deep-learning interpretable-ai explainable-ai interpretable-neural-networks interpretability-and-explainability
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Mar 27, 2025 - Python
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
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Nov 12, 2024 - Python
Explainable Speaker Recognition
forensics speaker-recognition resnet34 likelihood-ratio x-vector-pytorch interpretability-and-explainability automatic-voice-comparison forensic-speaker-recognition
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Oct 26, 2022 - Python
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
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Jan 17, 2023 - Python
Semi-supervised Concept Bottleneck Models (SSCBM)
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Mar 7, 2025 - Python
Recbole extension with focus on Knowledge Graphs (KGs) and interpretability/explainability.
recommender-systems link-prediction knowledge-graph-embeddings interpretability-and-explainability path-reasoning
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Apr 18, 2025 - Python
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Aug 16, 2024 - Python
Implementation of the gradient-based t-SNE sttribution method described in our GLBIO oral presentation: 'Towards Computing Attributions for Dimensionality Reduction Techniques'
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May 27, 2024 - Python
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