5 papers
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…
Disentanglement of Variations with Multimodal Generative Modeling
Yijie Zhang, Yiyang Shen, Weiran Wang
Multimodal data are prevalent across various domains, and learning robust representations of such data is paramount to enhancing generation quality and downstream task performance.…
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.…
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss
Yi-Shan Wu, Yijie Zhang, Badr-Eddine Chérief-Abdellatif +1
PAC-Bayesian analysis is a frequentist framework for incorporating prior knowledge into learning. It was inspired by Bayesian learning, which allows sequential data processing and…
If there is no underfitting, there is no Cold Posterior Effect
Yijie Zhang, Yi-Shan Wu, Luis A. Ortega +1
The cold posterior effect (CPE) (Wenzel et al., 2020) in Bayesian deep learning shows that, for posteriors with a temperature , the resulting posterior predictive could have b…