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On Deep Set Learning and the Choice of Aggregations., , , and . ICANN (1), volume 11727 of Lecture Notes in Computer Science, page 444-457. Springer, (2019)Approximate Bayesian Inference in Spatial Environments., , , , and . Robotics: Science and Systems, (2019)Learning Hierarchical Priors in VAEs., , , , and . NeurIPS, page 2866-2875. (2019)Latent Matters: Learning Deep State-Space Models., , , , and . NeurIPS, page 10234-10245. (2021)Dynamic movement primitives in latent space of time-dependent variational autoencoders., , and . Humanoids, page 629-636. IEEE, (2016)On Fast Dropout and its Applicability to Recurrent Networks., , , , and . ICLR (Poster), (2014)Solving the Ill-Conditioning in Neural Network Learning., and . Neural Networks: Tricks of the Trade, volume 1524 of Lecture Notes in Computer Science, Springer, (1996)Probabilistic Dalek - Emulator framework with probabilistic prediction for supernova tomography., , , , and . CoRR, (2022)Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models., , , , and . ICLR, OpenReview.net, (2021)Increasing the Generalisaton Capacity of Conditional VAEs., , , , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 779-791. Springer, (2019)