Gianluca Detommaso

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 13

Top Topics

Bayesian Inference

Dempster Shafer

Top Venues

SIAM/ASA J. Uncertain. Quantification

Publications

Simon Valentin, Jinmiao Fu, Gianluca Detommaso, Shaoyuan Xu, Giovanni Zappella, Bryan Wang
Cost-Effective Hallucination Detection for LLMs. CoRR (2024)
Gianluca Detommaso, Martín Bertrán, Riccardo Fogliato, Aaron Roth
Multicalibration for Confidence Scoring in LLMs. CoRR (2024)
Luca Franceschi, Cemre Zor, Muhammad Bilal Zafar, Gianluca Detommaso, Cédric Archambeau, Tamas Madl, Michele Donini, Matthias W. Seeger
Explaining Multiclass Classifiers with Categorical Values: A Case Study in Radiography. TML4H (2023)
Gianluca Detommaso, Alberto Gasparin, Michele Donini, Matthias W. Seeger, Andrew Gordon Wilson, Cédric Archambeau
Fortuna: A Library for Uncertainty Quantification in Deep Learning. CoRR (2023)
Gianluca Detommaso, Alberto Gasparin, Andrew Wilson, Cédric Archambeau
Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors. CoRR (2022)
Gianluca Detommaso, Michael Brückner, Philip Schulz, Victor Chernozhukov
Causal Bias Quantification for Continuous Treatment. CoRR (2021)
Jakob Kruse, Gianluca Detommaso, Ullrich Köthe, Robert Scheichl
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference. AAAI (2021)
Tiangang Cui, Gianluca Detommaso, Robert Scheichl
Multilevel Dimension-Independent Likelihood-Informed MCMC for Large-Scale Inverse Problems. CoRR (2019)
Gianluca Detommaso, Tim J. Dodwell, Robert Scheichl
Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies. SIAM/ASA J. Uncertain. Quantification 7 (1) (2019)
Gianluca Detommaso, Jakob Kruse, Lynton Ardizzone, Carsten Rother, Ullrich Köthe, Robert Scheichl
HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference. CoRR (2019)
Gianluca Detommaso, Hanne Hoitzing, Tiangang Cui, Ardavan Alamir
Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks. CoRR (2019)
Gianluca Detommaso, Tiangang Cui, Youssef M. Marzouk, Alessio Spantini, Robert Scheichl
A Stein variational Newton method. NeurIPS (2018)
Gianluca Detommaso, Tiangang Cui, Youssef M. Marzouk, Robert Scheichl, Alessio Spantini
A Stein variational Newton method. CoRR (2018)