publications

2024

2024

  1. ICLR 2024
    How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
    Lorenzo Pacchiardi ,  Alex James Chan ,  Sören Mindermann ,  Ilan Moscovitz ,  Alexa Yue Pan ,  Yarin Gal ,  Owain Evans ,  and  Jan M. Brauner
    2024

2022

2022

  1. arXiv
    Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization
    Lorenzo Pacchiardi ,  and  Ritabrata Dutta
    arXiv preprint arXiv:2205.15784, 2022
  2. arXiv
    Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization
    Lorenzo Pacchiardi ,  Rilwan Adewoyin ,  Peter Dueben ,  and  Ritabrata Dutta
    arXiv preprint arXiv:2112.08217, 2022
  3. JMLR
    Score Matched Neural Exponential Families for Likelihood-Free Inference
    Lorenzo Pacchiardi ,  and  Ritabrata Dutta
    Journal of Machine Learning Research, 2022

2021

2021

  1. arXiv
    Generalized Bayesian Likelihood-Free Inference Using Scoring Rules Estimators
    Lorenzo Pacchiardi ,  and  Ritabrata Dutta
    arXiv preprint arXiv:2104.03889, 2021
  2. PLOS Comp. Biol.
    Using Mobility Data in the Design of Optimal Lockdown Strategies for the COVID-19 Pandemic
    Ritabrata Dutta ,  Susana Gomes ,  Dante Kalise ,  and  Lorenzo Pacchiardi
    PLOS Computational Biology, 2021
  3. JSS
    ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation
    Ritabrata Dutta ,  Marcel Schoengens ,  Lorenzo Pacchiardi ,  Avinash Ummadisingu ,  Nicole Widmer ,  Pierre Künzli ,  Jukka-Pekka Onnela ,  and  Antonietta Mira
    Journal of Statistical Software, 2021

2020

2020

  1. Sankhya B
    Distance-Learning for Approximate Bayesian Computation to Model a Volcanic Eruption
    Lorenzo Pacchiardi ,  Pierre Künzli ,  Marcel Schoengens ,  Bastien Chopard ,  and  Ritabrata Dutta
    Sankhya B, 2020