A Stein variational Newton method. - Gianluca Detommaso; Tiangang Cui; Youssef M. Marzouk; Alessio Spantini; Robert Scheichl (NeurIPS, 2018)

Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks. - Gianluca Detommaso; Hanne Hoitzing; Tiangang Cui; Ardavan Alamir (CoRR, 2019)

HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. - Gianluca Detommaso; Jakob Kruse; Lynton Ardizzone; Carsten Rother; Ullrich Köthe; Robert Scheichl (CoRR, 2019)

Multilevel Dimension-Independent Likelihood-Informed MCMC for Large-Scale Inverse Problems. - Tiangang Cui; Gianluca Detommaso; Robert Scheichl (CoRR, 2019)

Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies. - Gianluca Detommaso; Tim J. Dodwell; Robert Scheichl (SIAM/ASA J. Uncertain. Quantification, 2019)

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. - Jakob Kruse; Gianluca Detommaso; Ullrich Köthe; Robert Scheichl (AAAI, 2021)

Causal Bias Quantification for Continuous Treatment. - Gianluca Detommaso; Michael Brückner; Philip Schulz; Victor Chernozhukov (CoRR, 2021)

Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors. - Gianluca Detommaso; Alberto Gasparin; Andrew Wilson; Cédric Archambeau (CoRR, 2022)

Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography. - Luca Franceschi 001; Cemre Zor; Muhammad Bilal Zafar; Gianluca Detommaso; Cédric Archambeau; Tamas Madl; Michele Donini; Matthias W. Seeger (TML4H, 2023)

Distance-aware Calibration for Pre-trained Language Models. - Alberto Gasparin; Gianluca Detommaso (EMNLP (Findings), 2024)

Multicalibration for Confidence Scoring in LLMs. - Gianluca Detommaso; Martin Bertran Lopez; Riccardo Fogliato; Aaron Roth 001 (ICML, 2024)

Multicalibration for Confidence Scoring in LLMs. - Gianluca Detommaso; Martín Bertrán; Riccardo Fogliato; Aaron Roth 001 (CoRR, 2024)

Cost-Effective Hallucination Detection for LLMs. - Simon Valentin; Jinmiao Fu; Gianluca Detommaso; Shaoyuan Xu; Giovanni Zappella; Bryan Wang (CoRR, 2024)

Fortuna: A Library for Uncertainty Quantification in Deep Learning. - Gianluca Detommaso; Alberto Gasparin; Michele Donini; Matthias W. Seeger; Andrew Gordon Wilson; Cédric Archambeau (J. Mach. Learn. Res., 2024)