Code for the paper "Post-hoc Concept Bottleneck Models". Spotlight @ ICLR 2023

Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper "Learning to Receive Help: Intervention-Aware Concept Embedding Models"

This is a list of awesome prototype-based papers for explainable artificial intelligence.

Learning Bottleneck Concepts in Image Classification (CVPR 2023)

ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

The Concept Bottleneck Shift Detection (CBSD) methods for explaining and detecting various dataset shifts.

Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.

Code for the paper "Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis", CVPRW 2023.

This repository contains the implementation of Concept Activation Regions, a new framework to explain deep neural networks with human concepts. For more details, please read our NeurIPS 2022 paper: 'Concept Activation Regions: a Generalized Framework for Concept-Based Explanations.

Official Implementation of TMLR's paper: "TabCBM: Concept-based Interpretable Neural Networks for Tabular Data"

Prototypical Concept-based Explanations, accepted at SAIAD workshop at CVPR 2024.

Code for the paper "Towards Concept-based Interpretability of Skin Lesion Diagnosis using Vision-Language Models", ISBI 2024.

all interview questions based on frontend, backend, and data structures and algorithms (DSA) topics can be quite extensive