System for Medical Concept Extraction and Linking

CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph.

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

[ECCV 2024 Oral] ConceptExpress: Harnessing Diffusion Models for Single-image Unsupervised Concept Extraction

Flexible and powerful platform for biomedical information extraction from text

Explainability of Deep Learning Models

Code for the paper: Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery. ECCV 2024.

Tools for Formal Concept Analysis

MEME: Generating RNN Model Explanations via Model Extraction

CME: Concept-based Model Extraction

CoCo-Ex extracts meaningful concepts from natural language texts and maps them to conjunct concept nodes in ConceptNet, utilizing the maximum of relational information stored in the ConceptNet knowledge graph.

Simple spaCy-based concept extraction API, involving a dictionary of relevant concepts.

Combining Energy-Based Modeling and RL to solve the challenging Abstract Reasoning Corpus[1] tasks.

create concept map from textbook data

Software created within Accumulate project (www.accumulate.be) at CLiPS, University of Antwerp

Retrospective Extraction of Visual and Logical Insights for Ontology-based interpretation of Neural Networks

Python code for construction and analysis of semantic networks from text.

REST-API for LearningMiner.

A toolkit to do concept expansion via search engine snippet