Bibliography
References
- Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., Desmaison, A., Kopf, A., Yang, E., DeVito, Z., Raison, M., Tejani, A., Chilamkurthy, S.
- Gardner, J.R., Pleiss, G., Bindel, D., Weinberger, K.Q. and Wilson, A.G. (2018). GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration. In Advances in Neural Information Processing Systems.
- Rasmussen, C.E. and Williams, C.K.I. (2005). Gaussian Processes for Machine Learning. The MIT Press. doi:10.7551/mitpress/3206.001.0001
- Bishop, C.M. (1994). Mixture Density Networks. Aston University.
- Titsias, M. (2009). Variational Learning of Inducing Variables in Sparse Gaussian Processes. In Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, vol. 5, pp. 567--574. https://proceedings.mlr.press/v5/titsias09a.html