Build flexible hierarchical multi-instance learning models.

PyTorch code for JEREX: Joint Entity-Level Relation Extractor

Machine learning with Mill.jl for JSON documents

[ICME 2025 Oral] Official implementation of "GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection"

[MICCAI'23] HIGT: Hierarchical Interaction Graph-Transformer for Whole Slide Image Analysis

[EMNLP 2020] Multi-Instance Multi-Label Learning Networks for Aspect-Category Sentiment Analysis

Implementation of "Dynamic Policy-Driven Adaptive Multi-Instance Learning for Whole Slide Image Classification", (CVPR 2024 Highlight).

Multi-Instance Causal Representation Learning

Code for the paper: Mixed Models with Multiple Instance Learning

Official code repository of paper HMIL: Hierarchical Multi-Instance Learning for Fine-Grained WSI Classification

Code and dataset for TACL 19: Weakly Supervised Domain Detection.

A curated list of awesome Multi-instance Learning frameworks for Whole Slide Images (WSIs) classification, segmentation, etc.

Advanced Machine Learning Algorithms including Cost-Sensitive Learning, Class Imbalances, Multi-Label Data, Multi-Instance Learning, Active Learning, Multi-Relational Data Mining, Interpretability in Python using Scikit-Learn.

This repository contains some comprehensive approaches for the purpose of classifying breast cancer tissue using whole slide images (WSIs).

Data-to-Text generation with loosely aligned WikiBio dataset from (Lebret et al. 2016). Explicit content selection step with Multi-Instance Learning.

Multi-instance CNN for Breast Cancer Classification

[ISMB 2024] Official PyTorch Code for "PhiHER2: Phenotype-informed weakly supervised model for HER2 status prediction from WSIs"

A deployment project of an ML pipeline using AWS EC2 and AWS Lambda

Python library to train Multi Instance Learning algorithms in histology for custom tasks.