Ryan Kelly

PhD student at QUT in computational Bayesian statistics

[SIAM Activity Group on Dynamical Systems @DynamicsSIAM]

"A Comprehensive Guide to Simulation-based Inference in Computational Biology" (by Xiaoyu Wang, Ryan P. Kelly, Adrianne L. Jenner, David J. Warne, Christopher Drovandi): https://t.co/tZQNGGZn42

[Umberto Picchini @uPicchini]

tweeting this so I can also find it again.

Pen and Paper exercises in ML *WITH SOLUTIONS*

By Michael Gutmann

https://t.co/lPucR3Iuw9

[Ryan Kelly @RP_Kelly98]

@betanalpha Steps 1 - 3 seem similar to some steps in simulation-based inference, namely generating simulations from an assumed data generating process. But unsure of a nice name for the full process here, perhaps simulation-based model checks?

[Ryan Kelly @RP_Kelly98]

Excited to see our paper accepted in TMLR. This work, a collaborative effort with David Nott, @dtfraz, @DavidJWarne, and @chris_drovandi, proposes robust sequential neural likelihood, a simulation-based inference method that is robust to model misspecification.

[Accepted papers at TMLR @TmlrPub]

Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference

Ryan P. Kelly, David J Nott, David Tyler Frazier, David J Warne, Christopher Drovandi.

Action editor: George Papamakarios.

https://t.co/k3mWsSfDw4

#models #likelihoods #like

[Chris Drovandi @chris_drovandi]

New pre-print by PhD student @RyanKel26511337 on how to make a recent neural approach to simulation-based inference robust to misspecification. @dtfraz @DavidJWarne @QUTDataScience

https://t.co/oCrWtfEe9w