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Deep Learning with Bayesian Principles. (2019)A Generalization Bound for Online Variational Inference., , and . ACML, volume 101 of Proceedings of Machine Learning Research, page 662-677. PMLR, (2019)Structured second-order methods via natural gradient descent., , , and . CoRR, (2021)AI for the Social Good (Dagstuhl Seminar 19082)., , , and . Dagstuhl Reports, 9 (2): 111-122 (2019)Expectation-maximization (EM) algorithm for instantaneous frequency estimation with Kalman smoother., and . EUSIPCO, page 1797-1800. IEEE, (2004)Conformal Prediction via Regression-as-Classification., , , , and . CoRR, (2024)Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam., , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 2616-2625. PMLR, (2018)Scalable Training of Inference Networks for Gaussian-Process Models., , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5758-5768. PMLR, (2019)Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models., , , and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 951-959. JMLR.org, (2013)Subset-of-data variational inference for deep Gaussian-processes regression., , and . UAI, volume 161 of Proceedings of Machine Learning Research, page 1362-1370. AUAI Press, (2021)