bezirganyan/DBF_uncertainty
Original PyTorch implementation of AIStats 2025 paper: Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
This is a research project for AI/ML practitioners working on multimodal learning. It helps by providing a PyTorch implementation for combining information from different data sources (like images and text) while also quantifying how certain the model is about its predictions. You input multimodal datasets, and it outputs model training results and uncertainty metrics. This is for researchers and advanced practitioners developing new machine learning models.
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Use this if you are a machine learning researcher exploring novel methods for fusing multimodal data and need to understand the uncertainty in your model's predictions.
Not ideal if you are looking for a plug-and-play solution for a business problem or a library with high-level APIs for immediate application.
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10
Forks
1
Language
Python
License
GPL-3.0
Last pushed
Sep 12, 2025
Commits (30d)
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