12 citations · 38 across the 9 of their papers we have counts for
4 papers · 1 filter
Robust and Scalable Bayesian Online Changepoint Detection
Matias Altamirano, François-Xavier Briol, Jeremias Knoblauch
This paper proposes an online, provably robust, and scalable Bayesian approach for changepoint detection. The resulting algorithm has key advantages over previous work: it provides…
Composite Goodness-of-fit Tests with Kernels
Oscar Key, Arthur Gretton, François-Xavier Briol +1
Model misspecification can create significant challenges for the implementation of probabilistic models, and this has led to development of a range of robust methods which directly…
The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks
Takuo Matsubara, Chris J. Oates, François-Xavier Briol
Bayesian neural networks attempt to combine the strong predictive performance of neural networks with formal quantification of uncertainty associated with the predictive output in…
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization
Shijing Si, Chris. J. Oates, Andrew B. Duncan +2
Control variates are a well-established tool to reduce the variance of Monte Carlo estimators. However, for large-scale problems including high-dimensional and large-sample setting…