Gianluca Detommaso

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All published works

Action	Title	Year	Authors
+ PDF Chat	Multicalibration for Confidence Scoring in LLMs	2024	Gianluca Detommaso Martín Bertrán Riccardo Fogliato Aaron Roth
+ PDF Chat	Multilevel dimension-independent likelihood-informed MCMC for large-scale inverse problems	2024	Tiangang Cui Gianluca Detommaso Robert Scheichl
+	Fortuna: A Library for Uncertainty Quantification in Deep Learning	2023	Gianluca Detommaso Alberto Gasparin Michele Donini Matthias Seeger Andrew Gordon Wilson Cédric Archambeau
+	Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors	2022	Gianluca Detommaso Alberto Gasparin A. S. Wilson Cédric Archambeau
+	Causal Bias Quantification for Continuous Treatment.	2021	Gianluca Detommaso Michael Brückner Philip Schulz Victor Chernozhukov
+ PDF Chat	HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference	2021	Jakob Kruse Gianluca Detommaso Ullrich Köthe Robert Scheichl
+	Causal Bias Quantification for Continuous Treatments	2021	Gianluca Detommaso Michael Brückner Philip Schulz Victor Chernozhukov
+	HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference.	2019	Gianluca Detommaso Jakob Kruse Lynton Ardizzone Carsten Rother Ullrich Köthe Robert Scheichl
+	HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference.	2019	Jakob Kruse Gianluca Detommaso Ullrich Köthe Robert Scheichl
+	Stein Variational Online Changepoint Detection with Applications to Hawkes Processes and Neural Networks	2019	Gianluca Detommaso Hanne Hoitzing Tiangang Cui A.S.A. Alamir
+ PDF Chat	Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies	2019	Gianluca Detommaso Tim Dodwell Robert Scheichl
+	Multilevel Dimension-Independent Likelihood-Informed MCMC for Large-Scale Inverse Problems	2019	Tiangang Cui Gianluca Detommaso Robert Scheichl
+	HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference	2019	Jakob Kruse Gianluca Detommaso Ullrich Köthe Robert Scheichl
+	A Stein variational Newton method	2018	Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl
+	Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies	2018	Gianluca Detommaso Tim Dodwell Robert Scheichl
+	A Stein variational Newton method	2018	Gianluca Detommaso Tiangang Cui Youssef Marzouk Alessio Spantini Robert Scheichl
+	Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies	2018	Gianluca Detommaso Tim Dodwell Robert Scheichl
+	A Stein variational Newton method	2018	Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl

Common Coauthors

Coauthor	Papers Together
Robert Scheichl	12
Tiangang Cui	6
Jakob Kruse	4
Ullrich Köthe	4
Youssef Marzouk	3
Alessio Spantini	3
Tim Dodwell	3
Michael Brückner	2
Alberto Gasparin	2
Victor Chernozhukov	2
Cédric Archambeau	2
Aaron Roth	1
Riccardo Fogliato	1
Matthias Seeger	1
A.S.A. Alamir	1
Philip Schulz	1
Hanne Hoitzing	1
Lynton Ardizzone	1
A. S. Wilson	1
Andrew Gordon Wilson	1
Carsten Rother	1
Philip Schulz	1
Martín Bertrán	1
Michele Donini	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Optimal Transport: Old and New	2013	Cédric Villani	5
+	Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm	2016	Qiang Liu Dilin Wang	4
+	Variational Inference: A Review for Statisticians	2017	David M. Blei Alp Kucukelbir Jon McAuliffe	4
+	Sampling via Measure Transport: An Introduction	2016	Youssef Marzouk Tarek Moselhy Matthew Parno Alessio Spantini	3
+	A Stein variational Newton method	2018	Gianluca Detommaso Tiangang Cui Alessio Spantini Youssef Marzouk Robert Scheichl	3
+	Markov Chain Monte Carlo in Practice	1995	Walter R. Gilks Sylvia Richardson David J. Spiegelhalter	3
+ PDF Chat	Further analysis of multilevel Monte Carlo methods for elliptic PDEs with random coefficients	2013	Aretha L. Teckentrup Robert Scheichl Michael B. Giles Elisabeth Ullmann	2
+ PDF Chat	Likelihood-informed dimension reduction for nonlinear inverse problems	2014	Tiangang Cui J. L. Martín Youssef Marzouk A. Solonen Alessio Spantini	2
+	High-dimensional integration: The quasi-Monte Carlo way	2013	Josef Dick Frances Y. Kuo Ian H. Sloan	2
+ PDF Chat	Dimension-independent likelihood-informed MCMC	2015	Tiangang Cui Kody J. H. Law Youssef Marzouk	2
+	Neural Autoregressive Flows	2018	Chin-Wei Huang David Krueger Alexandre Lacoste Aaron Courville	2
+	HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference.	2019	Gianluca Detommaso Jakob Kruse Lynton Ardizzone Carsten Rother Ullrich Köthe Robert Scheichl	2
+	A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion	2012	James L. Martin Lucas C. Wilcox Carsten Burstedde Omar Ghattas	2
+	Approximate Bayesian Computation (ABC) in practice	2010	Katalin Csilléry Michaël G. B. Blum Oscar E. Gaggiotti Olivier François	2
+ PDF Chat	Inverse problems: A Bayesian perspective	2010	Andrew M. Stuart	2
+	Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients	2011	K. A. Cliffe Michael B. Giles Robert Scheichl Aretha L. Teckentrup	2
+	MaCow: Masked Convolutional Generative Flow	2019	Xuezhe Ma Xiang Kong Shanghang Zhang Eduard Hovy	2
+	Multilevel Quasi-Monte Carlo methods for lognormal diffusion problems	2016	Frances Y. Kuo Robert Scheichl Christoph Schwab Ian H. Sloan Elisabeth Ullmann	2
+	Normalizing Flows for Probabilistic Modeling and Inference	2019	George Papamakarios Eric Nalisnick Danilo Jimenez Rezende Shakir Mohamed Balaji Lakshminarayanan	2
+ PDF Chat	Approximation and sampling of multivariate probability distributions in the tensor train decomposition	2019	Sergey Dolgov Karim Anaya‐Izquierdo Colin Fox Robert Scheichl	2
+	Guided Image Generation with Conditional Invertible Neural Networks	2019	Lynton Ardizzone Carsten Lüth Jakob Kruse Carsten Rother Ullrich Köthe	2
+ PDF Chat	Multilevel Monte Carlo Path Simulation	2008	Michael B. Giles	2
+	NICE: Non-linear Independent Components Estimation	2014	Laurent Dinh David Krueger Yoshua Bengio	2
+	Stein Variational Gradient Descent as Gradient Flow	2017	Qiang Liu	2
+ PDF Chat	A Hierarchical Multilevel Markov Chain Monte Carlo Algorithm with Applications to Uncertainty Quantification in Subsurface Flow	2015	Tim Dodwell C. Ketelsen Robert Scheichl Aretha L. Teckentrup	2
+ PDF Chat	Monte Carlo Statistical Methods	2000	Hoon Kim Christian P. Robert George Casella	2
+ PDF Chat	Normalizing Flows: An Introduction and Review of Current Methods	2020	Ivan Kobyzev Simon J. D. Prince Marcus A. Brubaker	2
+	Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes	2013	Ke Zhou Hongyuan Zha Le Song	1
+	Finite Element Error Analysis of Elliptic PDEs with Random Coefficients and Its Application to Multilevel Monte Carlo Methods	2013	Julia Charrier Robert Scheichl Aretha L. Teckentrup	1
+	Gaussian Process Change Point Models	2010	Yunus Saatçi R.D. Turner Carl Edward Rasmussen	1
+	Bayesian calibration of a large‐scale geothermal reservoir model by a new adaptive delayed acceptance Metropolis Hastings algorithm	2011	Tiangang Cui Colin Fox Michael J. O’Sullivan	1
+	On-line changepoint detection and parameter estimation with application to genomic data	2011	François Caron Arnaud Doucet Raphaël Gottardo	1
+	Bayesian Nonparametric Modeling for Causal Inference	2010	Jennifer Hill	1
+ PDF Chat	On the ergodicity properties of some adaptive MCMC algorithms	2006	Christophe Andrieu Éric Moulines	1
+	Statistical Analysis With Missing Data	1989	Maureen Lahiff Roderick J. A. Little Donald B. Rubin	1
+	Unbiased Estimation with Square Root Convergence for SDE Models	2015	Chang-Han Rhee Peter W. Glynn	1
+ PDF Chat	Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods	2011	Mark Girolami Ben Calderhead	1
+	Inverse Problem Theory and Methods for Model Parameter Estimation	2005	Albert Tarantola	1
+ PDF Chat	Optimal Scaling of Discrete Approximations to Langevin Diffusions	1998	Gareth O. Roberts Jeffrey S. Rosenthal	1
+	The Propensity Score with Continuous Treatments	2004	Keisuke Hirano Guido W. Imbens	1
+	Space-Time Point-Process Models for Earthquake Occurrences	1998	Yosihiko Ogata	1
+	A general spline representation for nonparametric and semiparametric density estimates using diffeomorphisms	2012	Ethan Anderes Marc Coram	1
+ PDF Chat	Markov Chains for Exploring Posterior Distributions	1994	Luke Tierney	1
+ PDF Chat	Complexity analysis of accelerated MCMC methods for Bayesian inversion	2013	Viêt Hà Hòang Christoph Schwab Andrew M. Stuart	1
+ PDF Chat	Multilevel Monte Carlo methods	2015	Michael B. Giles	1
+ PDF Chat	The central role of the propensity score in observational studies for causal effects	1983	Paul R. Rosenbaum Donald B. Rubin	1
+ PDF Chat	Estimating Conditional Average Treatment Effects	2014	Jason Abrevaya Yu-Chin Hsu Robert P. Lieli	1
+	MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster	2013	Simon L. Cotter Gareth O. Roberts Andrew M. Stuart David White	1
+ PDF Chat	A Multilevel Monte Carlo Method for Computing Failure Probabilities	2016	Daniel Elfverson Fredrik Hellman Axel Målqvist	1
+ PDF Chat	An Adaptive Metropolis Algorithm	2001	Heikki Haario Eero Saksman J. Tamminen	1