Tag: uncertainty estimation
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Bayesian-LoRA: Probabilistic Adaptation for Large Language Models
Discover Bayesian-LoRA, a probabilistic low-rank adaptation method that improves calibration and uncertainty in large language models with minimal paramete...
Optimizing Medical Image Segmentation with Uncertainty Decisions
Explore how transforming uncertainty estimates into actionable decisions improves medical image segmentation accuracy and safety across datasets.
NERD Model Reveals Higher-Order Brain Representations in Neurofeedback
Discover how the NERD diffusion model explains human neurofeedback by characterizing higher-order brain representations and learning uncertainty.
Socrates Loss: Enhancing Confidence Calibration & Classification
Discover Socrates Loss, a unified approach improving confidence calibration and classification stability in deep neural networks for reliable AI.
Evidential Transformation Network for Efficient Uncertainty Estimation
Discover how Evidential Transformation Network converts pretrained models for accurate, lightweight post-hoc uncertainty estimation in vision and language...