Tag: Uncertainty Quantification
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MedFormer-UR: Uncertainty Transformer for Medical Imaging
MedFormer-UR enhances medical image classification with uncertainty quantification, improving accuracy and transparency across multiple imaging modalities.
Quantifying Uncertainty in LLM Multi-Agent Systems via Tensor
Discover how tensor decomposition quantifies uncertainty in LLM-based multi-agent systems, improving reliability across complex communication patterns.
VOLTA: Rethinking Auxiliary Losses in Deep Learning Calibration
Discover how VOLTA outperforms traditional UQ methods, proving auxiliary losses less effective for calibrated deep learning and OOD detection.
Bayesian Inference for Speech SNNs: Smoothing & Uncertainty
Explore Bayesian inference in speech SNNs for improved uncertainty quantification and smoother loss landscapes using the IVON method.
SELFDOUBT: Efficient Uncertainty Quantification for Reasoning LLMs
Discover SELFDOUBT, a novel method using the Hedge-to-Verify Ratio to quantify uncertainty in reasoning LLMs with high accuracy and low cost.