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Conjugate-Computation Variational Inference: Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models., and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 878-887. PMLR, (2017)Exploiting Inferential Structure in Neural Processes., , and . UAI, volume 216 of Proceedings of Machine Learning Research, page 2089-2098. PMLR, (2023)Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling., , , , , , and . AAAI, page 4602-4609. AAAI Press, (2020)Fast Variational Learning in State-Space Gaussian Process Models., , , and . MLSP, page 1-6. IEEE, (2020)Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling., , , and . AISTATS, volume 84 of Proceedings of Machine Learning Research, page 1108-1116. PMLR, (2018)Fast yet Simple Natural-Gradient Descent for Variational Inference in Complex Models., and . ISITA, page 31-35. IEEE, (2018)Practical Deep Learning with Bayesian Principles., , , , , , and . NeurIPS, page 4289-4301. (2019)Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 21026-21050. PMLR, (2023)Improving Continual Learning by Accurate Gradient Reconstructions of the Past., , , , , , and . Trans. Mach. Learn. Res., (2023)AI for the Social Good (Dagstuhl Seminar 19082)., , , and . Dagstuhl Reports, 9 (2): 111-122 (2019)