124 citations · 528 across the 41 of their papers we have counts for
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Vprop: Variational Inference using RMSprop
Mohammad Emtiyaz Khan, Zuozhu Liu, Voot Tangkaratt +1
Many computationally-efficient methods for Bayesian deep learning rely on continuous optimization algorithms, but the implementation of these methods requires significant changes t…
Variational Adaptive-Newton Method for Explorative Learning
Mohammad Emtiyaz Khan, Wu Lin, Voot Tangkaratt +2
We present the Variational Adaptive Newton (VAN) method which is a black-box optimization method especially suitable for explorative-learning tasks such as active learning and rein…
Bayesian Nonparametric Poisson-Process Allocation for Time-Sequence Modeling
Hongyi Ding, Mohammad Emtiyaz Khan, Issei Sato +1
Analyzing the underlying structure of multiple time-sequences provides insights into the understanding of social networks and human activities. In this work, we present the \emph{B…
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models
Mohammad Emtiyaz Khan, Wu Lin
Variational inference is computationally challenging in models that contain both conjugate and non-conjugate terms. Methods specifically designed for conjugate models, even though…