5 AISTATS 2020 Accepted Papers!

5 papers co-authored by the OxCSML group members have been accepted to the main program of AISTATS 2020

• A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments
  Adam Foster (University of Oxford); Martin Jankowiak (Uber AI Labs); Matthew O’Meara (University of Michigan); Yee Whye Teh (University of Oxford); Tom Rainforth (University of Oxford)

• Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components
  Chris Carmona (University of Oxford); Geoff Nicholls (University of Oxford)

• BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders Kaspar Märtens (University of Oxford), Christopher Yau (University of Manchester, The Alan Turing Institute)

• Neural Decomposition: Functional ANOVA with Variational Autoencoders Kaspar Märtens (University of Oxford), Christopher Yau (University of Manchester, The Alan Turing Institute)

• Non-exchangeable feature allocation models with sublinear growth of the feature sizes
  Giuseppe Di Benedetto (University of Oxford), Francois Caron (University of Oxford), Yee Whye Teh (University of Oxford)