Authors:
(1) Sarah Zhao, Department of Statistics, Stanford University, ([email protected]);
(2) Aditya Ravuri, Department of Computer Science, University of Cambridge ([email protected]);
(3) Vidhi Lalchand, Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard ([email protected]);
(4) Neil D. Lawrence, Department of Computer Science, University of Cambridge ([email protected]).
Table of Links
2. Background
2.1 Amortized Stochastic Variational Bayesian GPLVM
2.2 Encoding Domain Knowledge through Kernels
3. Our Model and Pre-Processing and Likelihood
4.1 Each Component is Crucial to Modifies Model Performance
4.3 Consistency of Latent Space with Biological Factors
4. Conclusion, Acknowledgement, and References
This paper is available on arxiv under CC BY-SA 4.0 DEED license.
