Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks."
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Updated
Apr 2, 2022 - Python
Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks."
Explainable Speaker Recognition
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.
MICCAI 2022 (Oral): Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis
[ICCV 2023] Learning Support and Trivial Prototypes for Interpretable Image Classification
Official code of "Discover and Cure: Concept-aware Mitigation of Spurious Correlation" (ICML 2023)
Implementation of the gradient-based t-SNE sttribution method described in our GLBIO oral presentation: 'Towards Computing Attributions for Dimensionality Reduction Techniques'
[KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"
Semi-supervised Concept Bottleneck Models (SSCBM)
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