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Latent Matters: Amortised Variational Inference With Constrained Optimisation and Learnable Priors.. Technical University of Munich, Germany, (2021)Continual Learning with Bayesian Neural Networks for Non-Stationary Data., , , , и . ICLR, OpenReview.net, (2020)Fast Approximate Geodesics for Deep Generative Models., , , , , и . ICANN (2), том 11728 из Lecture Notes in Computer Science, стр. 554-566. Springer, (2019)Learning Flat Latent Manifolds with VAEs., , , , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 1587-1596. PMLR, (2020)Learning Hierarchical Priors in VAEs., , , , и . NeurIPS, стр. 2866-2875. (2019)Latent Matters: Learning Deep State-Space Models., , , , и . NeurIPS, стр. 10234-10245. (2021)Increasing the Generalisaton Capacity of Conditional VAEs., , , , и . ICANN (2), том 11728 из Lecture Notes in Computer Science, стр. 779-791. Springer, (2019)