Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks, offering predictive uncertainty ...
The demand for uncertainty quantification in modern sequence modeling tasks has prompted researchers to explore deep integration between Bayesian inference and Transformer architectures, but existing ...
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