Replays

Monday, 12 April

Australian Session

Recording of the session is available here.

• Clara Grazian (University of New South Wales). Approximate Bayesian Conditional Copulas: slides

• David Nott (National University of Singapore). Detecting Conflicting Summary Statistics in Likelihood-free Inference: slides

• Hien Nguyen (La Trobe). Distance-based ABC Procedures: slides

• Robert Kohn (University of New South Wales). Robust Particle Density Tempering for StateSpace Models: slides

Joint Session - Computational

• Leah South (Queensland University of Technology). BSL: An R package for Bayesian Synthetic Likelihood and its Extensions: slides, recording

• Henri Pesonen (University of Oslo). ELFI: Engine for Likelihood-free Inference: recording

• Lorenzo Pacchiardi (University of Oxford). ABCpy: a Package for State-of-the-art Likelihood-Free Inference Techniques: recording

• Florence Forbes (Inria Grenoble). Approximate Bayesian Computation with Surrogate Posteriors: slides, recording

Methodology I

• Louis Raynal (Harvard University). Scalable Approximate Bayesian Computation for Growing Network Models via Extrapolated and Sampled Summaries: slides, recording

• Edwin Fong (University of Oxford). Martingale Posteriors: Bayesian Uncertainty via Imputation: slides, recording

• Justin Alsing (Stockholm University). Bayesian decision making under intractable likelihoods: slides, recording

Methodology II

• Cecilia Viscardi (University of Florence). A large deviation approach to approximate Bayesian computation: slides, recording

• Michael Gutmann (University of Edinburgh). Robust Optimisation Monte Carlo: slides, recording

• Ritabrata Dutta (University of Warwick). Score Matched Conditional Exponential Families for Likelihood-Free Inference: slides, recording

Tuesday, 13 April

Australian Session

Recording of the session is available here.

• Anthony Ebert (Università della Svizzera Italiana). Combined parameter and state inference for automatically calibrated ABC: slides

• Gael Martin (Monash University). Loss-based Variational Bayes Prediction:

• Matias Quiroz (University of Technology Sydney). Spectral Subsampling MCMC for Stationary Multivariate Time Series: slides

Joint Session - Computational

• David Frazier (Monash University). Synthetic Likelihood in Misspecified Models: slides, recording

• Chris Drovandi (Queensland University of Technology). To Summarise or Not to Summarise in Likelihood-Free Inference: slides, recording

• Olivier Zahm (Inria Grenoble). Data-free Dimension Reduction for Bayesian Inverse Problems: recording

• Grégoire Clarté (Université Paris Dauphine - PSL). Component Wise Approximate Bayesian Computation: slides

Methodology III

• Riccardo Corradin (University of Milano-Bicocca). Approximate estimation of latent random partitions: slides

• Marko Järvenpää (University of Oslo). Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC: slides, recording

• Pedro Rodrigues (Inria Saclay). Leveraging Global Parameters for Flow-based Neural Posterior Estimation: slides, recording