2 papers
quant-ph2026
Self-Supervised Learning with Noisy Dataset for Rydberg Microwave Sensors Denoising
Zongkai Liu, Qiming Ren, Wenguang Yang +11
We report a self-supervised deep learning framework for Rydberg sensors that enables single-shot noise suppression matching the accuracy of multi-measurement averaging. The framewo…
cs.LG2024
On Cold Posteriors of Probabilistic Neural Networks: Understanding the Cold Posterior Effect and A New Way to Learn Cold Posteriors with Tight Generalization Guarantees
Yijie Zhang
Bayesian inference provides a principled probabilistic framework for quantifying uncertainty by updating beliefs based on prior knowledge and observed data through Bayes' theorem.…