Build flexible hierarchical multi-instance learning models.
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Updated
Aug 31, 2026 - Julia
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.
[ISMB 2024] Official PyTorch Code for "PhiHER2: Phenotype-informed weakly supervised model for HER2 status prediction from WSIs"
Multi-instance CNN for Breast Cancer Classification
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.
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