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Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models.

, , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4372-4381. PMLR, (2019)

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Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models., , и . ICML, том 97 из Proceedings of Machine Learning Research, стр. 4372-4381. PMLR, (2019)Neural Decomposition: Functional ANOVA with Variational Autoencoders., и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 2917-2927. PMLR, (2020)Disentangling shared and private latent factors in multimodal Variational Autoencoders., и . CoRR, (2024)Disentangling shared and private latent factors in multimodal Variational Autoencoders., и . MLCB, том 240 из Proceedings of Machine Learning Research, стр. 60-75. PMLR, (2023)Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models., , и . AISTATS, том 89 из Proceedings of Machine Learning Research, стр. 2359-2367. PMLR, (2019)Rarity: discovering rare cell populations from single-cell imaging data., , , , , и . Bioinform., (декабря 2023)Covariate Gaussian Process Latent Variable Models., , и . CoRR, (2018)Deep Stochastic Processes via Functional Markov Transition Operators., , , , и . CoRR, (2023)BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders., и . AISTATS, том 108 из Proceedings of Machine Learning Research, стр. 2928-2937. PMLR, (2020)Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries., , , , , , и . CoRR, (мая 2025)