| A | B | C | D | E | |
|---|---|---|---|---|---|
1 | TIME ZONE | Monday 12 April | |||
2 | LONDON (UTC +1) | PARIS (UTC +2) | AEST (UTC +10) | ||
3 | 2:00 p.m. - 3:00 p.m. | Clara Grazian | Approximate Bayesian Conditional Copulas | ||
4 | David Nott | Detecting Conflicting Summary Statistics in Likelihood-free Inference | |||
5 | 3:30 p.m. - 4:30 p.m. | Hien Nguyen | Distance-based ABC Procedures | ||
6 | Robert Kohn | Robust Particle Density Tempering for StateSpace Models | |||
7 | Joint Session - Computational. Catalyst: Jukka Corander | ||||
8 | 8:00 a.m. - 10:00 a.m. | 9:00 a.m. - 11:00 a.m. | 5:00 p.m. - 7:00 p.m. | Leah South | An R package for Bayesian Synthetic Likelihood and its Extensions |
9 | Henri Pesonen | Engine for Likelihood-free Inference | |||
10 | Lorenzo Pacchiardi | ABCpy: a Package for State-of-the-art Likelihood-Free Inference Techniques | |||
11 | Florence Forbes | Approximate Bayesian Computation with Surrogate Posteriors | |||
12 | Methodology I. Catalyst: Judith Rousseau | ||||
13 | 10:30 a.m. - 12:30 p.m. | 11:30 a.m. - 1:30 p.m. | Louis Raynal | Scalable Approximate Bayesian Computation for Growing Network Models via Extrapolated and Sampled Summaries | |
14 | Edwin Fong | Martingale Posteriors: Bayesian Uncertainty via Imputation | |||
15 | Justin Alsing | Bayesian decision making under intractable likelihoods | |||
16 | Methodology II. Catalyst: Dennis Prangle | ||||
17 | 2:30 p.m. - 4:30 p.m. | 3:30 p.m. - 5:30 p.m. | Cecilia Viscardi | A large deviation approach to approximate Bayesian computation | |
18 | Michael Gutmann | Robust Optimisation Monte Carlo | |||
19 | Ritabrata Dutta | Score Matched Conditional Exponential Families for Likelihood-Free Inference | |||
20 | |||||
21 | |||||
22 | |||||
23 | TIME ZONE | Tuesday 13 April | |||
24 | LONDON (UTC +1) | PARIS (UTC +2) | AEST (UTC +10) | ||
25 | 2:00 p.m. - 3:00 p.m. | Anthony Ebert | Combined parameter and state inference for automatically calibrated ABC | ||
26 | Jacob Priddle | Efficient Bayesian Synthetic Likelihood with Whitening Transformations | |||
27 | 3:30 p.m. - 4:30 p.m. | Gael Martin | Loss-based Variational Bayes Prediction | ||
28 | Matias Quiroz | Spectral Subsampling MCMC for Stationary Multivariate Time Series | |||
29 | Joint Session - Computational. Catalyst: Gael Martin | ||||
30 | 8:00 a.m. - 10:00 a.m. | 9:00 a.m. - 11:00 a.m. | 5:00 p.m. - 7:00 p.m. | David Frazier | Synthetic Likelihood in Misspecified Models: Consequences and Corrections |
31 | Chris Drovandi | To Summarise or Not to Summarise in Likelihood-Free Inference | |||
32 | Olivier Zahm | A Data Free Likelihood-Informed Subspace for Dimensionality Reduction of Bayesian Inverse Problems | |||
33 | Grégoire Clarté | Component Wise Approximate Bayesian Computation | |||
34 | Methodology III. Catalyst: Richard Everitt | ||||
35 | 10:30 a.m. - 12:30 p.m. | 11:30 a.m. - 1:30 p.m. | Riccardo Corradin | Approximate estimation of latent random partitions | |
36 | Marko Järvenpää | Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC | |||
37 | Pedro Rodrigues | Leveraging Global Parameters for Flow-based Neural Posterior Estimation | |||
38 | Replays. Catalyst: Robin Ryder | ||||
39 | 1:30 p.m. - 3:30 p.m. | 2:30 p.m. - 4:30 p.m. | Clara Grazian | Approximate Bayesian Conditional Copulas | |
40 | David Nott | Detecting Conflicting Summary Statistics in Likelihood-free Inference | |||
41 | Anthony Ebert | Combined parameter and state inference for automatically calibrated ABC | |||
42 | Jacob Priddle | Efficient Bayesian Synthetic Likelihood with Whitening Transformations | |||