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Learning Scalable Deep Kernels with Recurrent Structure., , , , and . CoRR, (2016)Product Kernel Interpolation for Scalable Gaussian Processes., , , , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1407-1416. PMLR, (2018)Learning Scalable Deep Kernels with Recurrent Structure., , , , and . J. Mach. Learn. Res., (2017)There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average., , , and . ICLR (Poster), OpenReview.net, (2019)The Case of Bayesian Deep Learning. (2019)Subspace Inference for Bayesian Deep Learning., , , , , and . UAI, volume 115 of Proceedings of Machine Learning Research, page 1169-1179. AUAI Press, (2019)Averaging Weights Leads to Wider Optima and Better Generalization., , , , and . UAI, page 876-885. AUAI Press, (2018)Fortuna: A Library for Uncertainty Quantification in Deep Learning., , , , , and . CoRR, (2023)What do Vision Transformers Learn? A Visual Exploration., , , , , , , and . CoRR, (2022)Non-Vacuous Generalization Bounds for Large Language Models., , , , , and . CoRR, (2023)