Skip to content

scottjingtt/awesome-interpretable-transfer-learning

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

13 Commits
 
 

Repository files navigation

Awesome Explainable/Interpretable Transfer Learning (XTL)

Awesome

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

Contents

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

Explainable/Interpretable Transfer Learning (XTL)

Conference

Journal

Preprints

Datasets

XAI

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

XTL

Lectures and Tutorials

Other Resources