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stat.ML2019★ 4 cited
Constructing the Matrix Multilayer Perceptron and its Application to the VAE
Jalil Taghia, Maria Bånkestad, Fredrik Lindsten +1
Like most learning algorithms, the multilayer perceptrons (MLP) is designed to learn a vector of parameters from data. However, in certain scenarios we are interested in learning s…
stat.ML2019
On the Convergence of Extended Variational Inference for Non-Gaussian Statistical Models
Zhanyu Ma, Jalil Taghia, Jun Guo
Variational inference (VI) is a widely used framework in Bayesian estimation. For most of the non-Gaussian statistical models, it is infeasible to find an analytically tractable so…
stat.ML2018
Conditionally Independent Multiresolution Gaussian Processes
Jalil Taghia, Thomas B. Schön
The multiresolution Gaussian process (GP) has gained increasing attention as a viable approach towards improving the quality of approximations in GPs that scale well to large-scale…