Meta graphical lasso: uncovering hidden interactions among latent mechanisms

Author:

Maruhashi Koji,Kashima Hisashi,Miyano Satoru,Park Heewon

Funder

Japan Society for the Promotion of Science

Publisher

Springer Science and Business Media LLC

Reference30 articles.

1. Kingma, D. P. & Welling, M. Auto-encoding variational Bayes. In ICLR (2014).

2. Kipf, T. N. & Welling, M. Variational graph auto-encoders. CoRR. arXiv:1611.07308 (2016).

3. Rezende, D. J., Mohamed, S. & Wierstra, D. Stochastic backpropagation and approximate inference in deep generative models. In ICML. 1278–1286 (2014).

4. Seninge, L., Anastopoulos, I., Ding, H. & Stuart, J. VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics. Nat. Commun. 12, 5684 (2021).

5. Qoku, A. & Buettner, F. Encoding domain knowledge in multi-view latent variable models: A bayesian approach with structured sparsity. In AISTATS. 11545–11562 (2023).

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