multiple-instance-learning
There are 74 repositories under multiple-instance-learning topic.
tcga_segmentation
Whole Slide Image segmentation with weakly supervised multiple instance learning on TCGA | MICCAI2020 https://arxiv.org/abs/2004.05024
PDL
Code for the paper " PDL: Regularizing Multiple Instance Learning with Progressive Dropout Layers "
pytorch_MELM
The pytorch implementation of the Min-Entropy Latent Model for Weakly Supervised Object Detection
DGR-MIL
Code for paper: DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification [ECCV 2024]
C2C
Implementation of Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification approach.
mil
Multiple instance learning library for Python
WENO
Official PyTorch implementation of our NeurIPS 2022 paper: Weakly Supervised Knowledge Distillation for Whole Slide Image Classification
Mixed_supervision
MICCAI2022: Multiple Instance Learning with Mixed Supervision in Gleason Grading.
ACMIL
Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification (ECCV2024)
Pipeline-Processing-TCGA-Slides-for-MIL
This repo provides the pipeline of processing TCGA whole-slide images for downstream multiple instance learning.
MICCAI2020mil
MICCAI2020. "Multiple Instance Learning with Center Embeddings for Histopathology Image Classification"
PseMix
[IEEE TMI 2024] Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
DGMIL
Official PyTorch implementation of our MICCAI 2022 paper: DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification.
AdvMIL
[MedIA 2024] The implementation of AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
CDMI-Net
The implementation of CDMI-Net in Paper - Deep Multiple Instance Learning for Landslide Mapping
LA_MIL
Implementation of LA_MIL, Local Attention Graph-based Transformer for WSIs, PyTorch
MIL-RBERT
MIL-RBERT: A Data-driven Approach for Noise Reduction in Distantly Supervised Biomedical Relation Extraction (BioNLP @ ACL 2020)
mimsi
Microsatellite Instability Classification using Multiple Instance Learning
MIL-SI
Official release of Shuffle Instances-based Vision Transformer for Pancreatic Cancer ROSE Image Classification
HAG-MIL
Repository for Hierarchical Attention-Guided Multiple Instance Learning
MUSTANG
Multi-stain graph self attention multiple instance learning for histopathology Whole Slide Images - BMVC 2023
MIL-Land-Cover-Classification
Code for the paper "Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification".
Thyroid-Cytopathological-Diagnosis-with-AMIL_MSFF
Attention Based Multi-Instance Thyroid Cytopathological Diagnosis with Multi-Scale Feature Fusion
MilGNet
MilGNet: Deep Multiple Instance Learning on Heterogeneous Graph for Drug-disease Association Prediction
INS
Official Pytorch Code of Our Paper: Rethinking Multiple Instance Learning for Whole Slide Image Classification: A Good Instance Classifier is All You Need
ProDiv
[CMPB 2024] ProDiv: Prototype-driven consistent pseudo-bag division for whole-slide image classification
SC-MIL
This repo for the paper titled "SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification"
UniqueClassCount
Pytorch implementation for ICLR 2020 paper "Weakly Supervised Clustering by Exploiting Unique Class Count"
ASC3
3ASC: variant prioritization tool leveraging multiple instance learning for rare Mendelian disease genomic testing
Cox_AMIL
Code for our BVM workshop submission "Attention-based Multiple Instance Learning for Survival Prediction on Lung Cancer Tissue Microarrays"
EquiVS
Employing Molecular Conformations for Ligand-based Virtual Screening with Equivariant Graph Neural Network and Deep Multiple Instance Learning
cDPMIL
[ECCV'24] cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Process
MS-DA-MIL-CNN
PyTorch implementation of MS-DA-MIL
attention-mechanism_distribution-regression
Code for the KDD 2019 workshop paper. Attention mechanism for distribution regression.
PathBench-MIL
PathBench-MIL: A comprehensive, flexible Benchmarking / AutoML framework for multiple instance learning in Histopathology