Awesome Explainable/Interpretable Transfer Learning (XTL)

Papers and resources collection about interpretable/explainable transfer learning (XTL)

Contents

• Awesome Explainable/Interpretable Transfer Learning (XTL)
• Contents
• Papers
  • Explainable/Interpretable AI (XAI)
  • Explainable/Interpretable Transfer Learning (XTL)
• Datasets
  • XAI
  • XTL
• Lectures and Tutorials
• Other Resources

Papers

Explainable/Interpretable AI (XAI)

Conference

• HIVE: Evaluating the Human Interpretability of Visual Explanations [2022 ECCV] [Github] [Project]
• B-cos Networks: Alignment is All We Need for Interpretability [2022 CVPR]
• HINT: Hierarchical Neuron Concept Explainer [2022 CVPR]
• Interpretable Part-Whole Hierarchies and Conceptual-Semantic Relationships in Neural Networks [2022 CVPR]
• Deformable_ProtoPNet_An_Interpretable_Image_Classifier_Using_Deformable_Prototypes [2022 CVPR]
• Proto2Proto: Can you recognize the car, the way I do? [2022 CVPR]
• Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation [2022 CVPR]
• Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors [2021 AAAI]
• Interpretable Compositional Convolutional Neural Networks [2021 IJCAI]
• Graph-based High-Order Relation Discovery for Fine-grained Recognition [2021 CVPR]
• Neural Prototype Trees for Interpretable Fine-grained Image Recognition [2021 CVPR]
• XProtoNet: Diagnosis in Chest Radiography with Global and Local Explanations [2021 CVPR]
• StyleMix: Separating Content and Style for Enhanced Data Augmentation [2021 CVPR]
• ProtoPShare: Prototypical Parts Sharing for Similarity Discovery in Interpretable Image Classification [2021 KDD]
• Towards Interpretable Deep Metric Learning with Structural Matching [2021 ICCV] [Code]
• Explaining in Style: Training a GAN to explain a classifier in StyleSpace [2021 ICCV] [Project] [Code]
• This Looks Like That: Deep Learning for Interpretable Image Recognition [2019 NIPS] [Code]
• Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks [2019 ICCV] [Code]
• Interpretable and Steerable Sequence Learning via Prototypes [2019 KDD]
• Interpretable Basis Decomposition for Visual Explanation [2018 ECCV]

Journal

• Hierarchical Prototype Learning for Zero-Shot Recognition [2019 TMM]

Preprint

Workshop

• This Looks Like That... Does it? Shortcomings of Latent Space Prototype Interpretability in Deep Networks [2021 ICML Workshop] [Github]

Explainable/Interpretable Transfer Learning (XTL)

Conference

• Independent Prototype Propagation for Zero-Shot Compositionality [2021 NIPS] [Code]
• ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation [2021 NIPS] [Code]
• Visualizing Adapted Knowledge in Domain Transfer [2021 CVPR] [Code]

Journal

Preprints

Datasets

XAI

• Caltech-UCSD Birds-200-2011 (CUB-200) [2011]

XTL

Lectures and Tutorials

Other Resources