Lorenzo Pacchiardi

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Ritabrata DuttaUniversity of WarwickVerified email at warwick.ac.uk
Peter DuebenRoyal Society University Research Fellow at the European Weather Centre (ECMWF)Verified email at ecmwf.int
Antonietta MiraProfessore di Statistica, Università della Svizzera italiana, LuganoVerified email at usi.ch
Jukka-Pekka "JP" OnnelaProfessor of Biostatistics, Harvard UniversityVerified email at hsph.harvard.edu
Owain EvansResearch Associate, University of OxfordVerified email at philosophy.ox.ac.uk
Jan BraunerUniversity of OxfordVerified email at cs.ox.ac.uk
Yarin GalAssociate Professor, University of OxfordVerified email at cs.ox.ac.uk
Sören MindermannUniversity of Oxford, OATMLVerified email at cs.ox.ac.uk
Alex J. ChanUniversity of CambridgeVerified email at cam.ac.uk
Mark FJ SteelProfessor of Statistics, University of WarwickVerified email at stats.warwick.ac.uk
David HukPhD student in Statistics, University of WarwickVerified email at warwick.ac.uk

Lorenzo Pacchiardi

Research Associate, University of Cambridge

Verified email at cam.ac.uk - Homepage

Large Language Models AI evaluation AI policy Bayesian Inference Likelihood-Free Inference


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ABCpy: A high-performance computing perspective to approximate Bayesian computation R Dutta, M Schoengens, L Pacchiardi, A Ummadisingu, N Widmer, ... Journal of Statistical Software 100 (7), 1-38, 2021	30*	2021
Using mobility data in the design of optimal lockdown strategies for the COVID-19 pandemic R Dutta, SN Gomes, D Kalise, L Pacchiardi PLoS Computational Biology 17 (8), e1009236, 2021	24	2021
Score matched neural exponential families for likelihood-free inference L Pacchiardi, R Dutta Journal of Machine Learning Research 23 (38), 1-71, 2022	23*	2022
Generalized Bayesian Likelihood-Free Inference L Pacchiardi, S Khoo, R Dutta arXiv preprint arXiv:2104.03889, 2021	22	2021
Distance-learning for approximate Bayesian computation to model a volcanic eruption L Pacchiardi, P Künzli, M Schöngens, B Chopard, R Dutta Sankhya B 83, 288-317, 2021	15	2021
Likelihood-free inference with generative neural networks via scoring rule minimization L Pacchiardi, R Dutta arXiv preprint arXiv:2205.15784, 2022	13	2022
How to catch an ai liar: Lie detection in black-box llms by asking unrelated questions L Pacchiardi, AJ Chan, S Mindermann, I Moscovitz, AY Pan, Y Gal, ... arXiv preprint arXiv:2309.15840, 2023	12	2023
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization L Pacchiardi, RA Adewoyin, P Dueben, R Dutta Journal of Machine Learning Research 25 (45), 1-64, 2024	11*	2024
Statistical inference in generative models using scoring rules L Pacchiardi University of Oxford, 2022	1	2022
David Huk, Lorenzo Pacchiardi, Ritabrata Dutta and Mark Steel's contribution to the Discussion of ‘Martingale posterior distributions’ by Fong, Holmes and Walker D Huk, L Pacchiardi, R Dutta, M Steel Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2023		2023

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