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Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data.

, , , и . CoRR, (2020)

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Li Li

Li Li

Li Li

Li Li

Li Li

 

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A Deep Generative Model for Disentangled Representations of Sequential Data., и . CoRR, (2018)Variational Continual Learning., , , и . CoRR, (2017)Deep Gaussian Processes for Regression using Approximate Expectation Propagation, , , , и . (2016)cite arxiv:1602.04133.Challenges and Perspectives in Deep Generative Modeling (Dagstuhl Seminar 23072)., , , , и . Dagstuhl Reports, 13 (2): 47-70 (февраля 2023)Approximate inference: new visions.. University of Cambridge, UK, (2018)British Library, EThOS.Sparse Uncertainty Representation in Deep Learning with Inducing Weights., , , и . NeurIPS, стр. 6515-6528. (2021)Meta-Learning Divergences for Variational Inference., , , , и . AISTATS, том 130 из Proceedings of Machine Learning Research, стр. 4024-4032. PMLR, (2021)Variational Implicit Processes., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4222-4233. PMLR, (2019)Dropout Inference in Bayesian Neural Networks with Alpha-divergences., и . ICML, том 70 из Proceedings of Machine Learning Research, стр. 2052-2061. PMLR, (2017)Meta-Learning For Stochastic Gradient MCMC., , и . ICLR (Poster), OpenReview.net, (2019)