When: 24-25 October 2022
Where: Sydney Business School Level 10, 1 Macquarie Place, Sydney
About: This workshop aims to bring together researchers in the region that are interested in topics at the interface of deep learning and statistics. It will be based around a set of talks, and there will be time for discussion and networking between the talks. The workshop, which is an in-person event, is 1.5 days long, and will finish at noon on the 25th October. Refreshments and lunch on the 24th October are provided. Space is limited; please let us know at azm@uow.edu.au if you register, plans change, and you need to cancel registration.
Registration: The workshop is now very close to, or at, capacity, so the registration page has been closed. If you’d still like to attend, please send me an e-mail directly (azm@uow.edu.au) to check availability. (The workshop is free of charge).
Workshop Programme
Monday 24th October
08:30: Coffee
09:00: Maurizio Filippone (EURECOM): Functional priors for Bayesian deep learning
10:00: Michael Smith (UMelb): Marginally Calibrated Deep Distributional Regression
10:35: Coffee Break
11:10: Laura Cartwright (UOW): Emulation of Lagrangian particle dispersion model sensitivities using a variational autoencoder
11:45: Edwin Bonilla (CSIRO): Scalable inference in Gaussian process and deep Gaussian process
models
12:20: Lunch
13:30: Laurent Jospin (UWA): Hands-on Bayesian neural networks - A tutorial for deep learning users
14:05: Luca Maestrini (ANU): Streamlined variational approximations for sparse linear mixed model
selection
14:40: Coffee Break
15:15: Laurence Davies (QUT): Flow-enhanced transdimensional proposals
15:50: Quan Vu (UOW): Warped gradient-enhanced Gaussian process surrogate models
16:25: Close
18:00: Dinner (Chat Thai)
Tuesday 25th October
08:30: Coffee
09:00: Minh-Ngoc Tran (USyd): Bayesian deep net GLM and GLMM
09:35: Daniel Schmidt (Monash): Log-scale prior distributions for adaptive shrinkage
10:10: Coffee Break
10:40: Clara Grazian (USyd): Assessing the invertibility of deep biometric representations
11:15: Andrew Zammit Mangion (UOW): Deep neural Bayes estimators for spatial models
11:50: Close
Acknowledgements
This event is supported by the Australian Research Council (ARC DE180100203).
Image credit: Pratyeka. The header image is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.
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