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stat.ML2019★ 9 cited
The Neural Moving Average Model for Scalable Variational Inference of State Space Models
Tom Ryder, Dennis Prangle, Andrew Golightly +1
Variational inference has had great success in scaling approximate Bayesian inference to big data by exploiting mini-batch training. To date, however, this strategy has been most a…
stat.ML2018★ 2 cited
Black-Box Autoregressive Density Estimation for State-Space Models
Tom Ryder, Andrew Golighty, A. Stephen McGough +1
State-space models (SSMs) provide a flexible framework for modelling time-series data. Consequently, SSMs are ubiquitously applied in areas such as engineering, econometrics and ep…