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Medical image analysis models can exhibit performance disparities across patient subgroups, threatening clinical safety and fairness. Existing methods typically address this issue by optimizing…

Post-training quantization (PTQ) is an attractive approach for compressing diffusion models to speed up the sampling process and reduce the memory footprint. Most existing PTQ methods uniformly...

Solution for addressing real-world image classification challenges. Human-AI collaborative classification (HAI-CC) aims to synergise the efficiency of…

Human-AI cooperative classification (HAI-CC) approaches aim to develop hybrid intelligent systems that enhance decision-making in various high-stakes real-world scenarios by leveraging both human expe...

Probabilistic learning to defer. Contribute to cnguyen10/pl2d development by creating an account on GitHub.

Project Overview Current generic AI models for mammogram analysis provide biased results for patients and inflexible analysis for radiologists, reducing patients’ and radiologists’ trust in such model...

Recent progress in machine learning research is gradually shifting its focus towards *human-AI cooperation* due to the advantages of exploiting the reliability of human experts and the efficiency...