280 citations · 1.1k across the 43 of their papers we have counts for
4 papers · 1 filter
Variational Continual Learning
Cuong V. Nguyen, Yingzhen Li, Thang D. Bui +1
This paper develops variational continual learning (VCL), a simple but general framework for continual learning that fuses online variational inference (VI) and recent advances in…
Gradient Estimators for Implicit Models
Yingzhen Li, Richard E. Turner
Implicit models, which allow for the generation of samples but not for point-wise evaluation of probabilities, are omnipresent in real-world problems tackled by machine learning an…
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li, Yarin Gal
To obtain uncertainty estimates with real-world Bayesian deep learning models, practical inference approximations are needed. Dropout variational inference (VI) for example has bee…
Approximate Inference with Amortised MCMC
Yingzhen Li, Richard E. Turner, Qiang Liu
We propose a novel approximate inference algorithm that approximates a target distribution by amortising the dynamics of a user-selected MCMC sampler. The idea is to initialise MCM…