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Torchmil: A PyTorch-based library for deep multiple instance learning

delete2026-03-10
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F
Francisco M. Castro-Macías *
F
Francisco Javier Sáez-Maldonado
P
Pablo Morales-Álvarez
R
Rafael Molina
DOI:10.1016/j.neucom.2026.133286delete
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Abstract

Abstract

En 中文
Multiple Instance Learning (MIL) is a powerful framework for weakly supervised learning, particularly useful when fine-grained annotations are unavailable. Despite growing interest in deep MIL methods, the field lacks standardized tools for model development, evaluation, and comparison, which hinders reproducibility and accessibility. To address this, we present torchmil, an open-source Python library built on PyTorch. torchmil offers a unified, modular, and extensible framework, featuring basic building blocks for MIL models, a standardized data format, and a curated collection of benchmark datasets and models. The library includes comprehensive documentation and tutorials to support both practitioners and researchers. torchmil aims to accelerate progress in MIL and lower the entry barrier for new users. Available at https://torchmil.readthedocs.io .
Keywords:
Multiple instance learning
Machine learning
Deep learning
Open source software
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Journal

Neurocomputing cover
Neurocomputing
IF:
6.5
Papers:
2.5W
Citations:
6.5W

Organization

U
University of Granada
Scholars:
2.3W
Papers: 1.9W
Citations: 24