Apr 17, 2024 We’ve launched, a portal to search academic jobs in Italy, boasting automated notifications for new openings! 🇮🇹
Mar 05, 2024 Our paper introducing a method to train generative networks for probabilistic forecasting using scoring rules has been published in Journal of Machine Learning Research! :champagne:
Feb 01, 2024 I co-authored an op-ed on the OECD.AI policy website about how an exemption for “therapeutic purposes” in the EU AI Act could serve as a loophole.
Jan 16, 2024 Our paper How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions has been accepted at ICLR 2024! :tada:
Aug 01, 2023 I am happy to communicate that I will join the Leverhulme Centre for the Future of Intelligence at the University of Cambridge in October 2023 :smile:
Jul 15, 2023 Today, I formally graduated from my PhD at Oxford! :smile:
Dec 20, 2022 I won a travel award at the International Conference for Statistics and Data Science by the Institute of Mathematical Statistics. I really enjoyed the opportunity to present my work there!
Nov 17, 2022 On the 9th of November, I successfully defended my PhD thesis :champagne:. A profound thanks to my examiners Chris Holmes and Chris Oates for their insightful comments and suggestions.
Jun 03, 2022 I have two preprints on arXiv exploring an alternative to adversarial training to train generative networks; the first applies it to probabilistic forecasting, while the second is concerned with Likelihood-Free Inference. I feel that is a promising overlooked approach. Happy to hear any feedback! :smile:
Mar 16, 2022 I have created a website aimed at listing works on using Neural Networks in Bayesian Likelihood-Free Inference :nerd_face: I have added the papers I am aware of, but please contribute others you may know (see “About” page for how).
Feb 03, 2022 Our paper discussing a new method for learning summary statistics for Approximate Bayesian Computation has been published in Journal of Machine Learning Research! :champagne:
Dec 04, 2021 Our paper describing the likelihood-free inference package ABCpy has been published in the Journal of Statistical Software! :tada: Check here for a quick YouTube video introducing the library.
Aug 12, 2021 Our optimal lockdown paper has finally been published by PLOS Computational Biology! :tada: Check the media coverage here!
Jul 06, 2021 If you missed my contributed talk on my work on “Generalized Bayesian likelihood-free inference using scoring rules estimators” at ISBA 2021 World Meeting, you can find the pre-recorded video here on YouTube.
Apr 09, 2021 I’ve just released a preprint on Generalized Bayesian Likelihood-Free Inference using Scoring rules with pseudo-marginal MCMC. We believe it is a promising bridge between these two lines of research. Preliminary version, feedback is welcome!
Feb 11, 2021 Our methodological paper on designing an optimal lockdown considering an epidemiological model has been accepted for publication by PLOS Computational Biology! :tada: :smile:
Dec 09, 2020 Our paper describing the likelihood-free inference package ABCpy has been accepted for publication in the Journal of Statistical Software! :tada: :smile: