Sequential design of computer experiments for the estimation of a probability of failure. - Julien Bect; David Ginsbourger; Ling Li; Victor Picheny; Emmanuel Vázquez (Stat. Comput., 2012)

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations. - Victor Picheny; David Ginsbourger (SIAM/ASA J. Uncertain. Quantification, 2013)

Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision. - Victor Picheny; David Ginsbourger; Yann Richet; Gregory Caplin (Technometrics, 2013)

Rejoinder. - Victor Picheny; David Ginsbourger; Yann Richet; Gregory Caplin (Technometrics, 2013)

A Stepwise uncertainty reduction approach to constrained global optimization. - Victor Picheny (AISTATS, 2014)

KrigInv: An efficient and user-friendly implementation of batch-sequential inversion strategies based on kriging. - Clément Chevalier; Victor Picheny; David Ginsbourger (Comput. Stat. Data Anal., 2014)

Noisy kriging-based optimization methods: A unified implementation within the DiceOptim package. - Victor Picheny; David Ginsbourger (Comput. Stat. Data Anal., 2014)

Fast Parallel Kriging-Based Stepwise Uncertainty Reduction With Application to the Identification of an Excursion Set. - Clément Chevalier; Julien Bect; David Ginsbourger; Emmanuel Vázquez; Victor Picheny; Yann Richet (Technometrics, 2014)

Multiobjective optimization using Gaussian process emulators via stepwise uncertainty reduction. - Victor Picheny (Stat. Comput., 2015)

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. - Victor Picheny; Robert B. Gramacy; Stefan M. Wild; Sébastien Le Digabel (NIPS, 2016)

Comment: Some Enhancements Over the Augmented Lagrangian Approach. - Victor Picheny; David Ginsbourger; Tipaluck Krityakierne (Technometrics, 2016)

Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise. - Hamed Jalali 002; Inneke Van Nieuwenhuyse; Victor Picheny (Eur. J. Oper. Res., 2017)

Targeting Well-Balanced Solutions in Multi-Objective Bayesian Optimization Under a Restricted Budget. - David Gaudrie; Rodolphe Le Riche; Victor Picheny; Benoit Enaux; Vincent Herbert (LION, 2018)

Budgeted Multi-Objective Optimization with a Focus on the Central Part of the Pareto Front - Extended Version. - David Gaudrie; Rodolphe Le Riche; Victor Picheny; Benoit Enaux; Vincent Herbert (CoRR, 2018)

Targeting Solutions in Bayesian Multi-Objective Optimization: Sequential and Parallel Versions. - David Gaudrie; Rodolphe Le Riche; Victor Picheny; Benoit Enaux; Vincent Herbert (CoRR, 2018)

Inferring large graphs using ℓ1 -penalized likelihood. - Magali Champion; Victor Picheny; Matthieu Vignes (Stat. Comput., 2018)

Correction to: Inferring large graphs using ℓ1-penalized likelihood. - Magali Champion; Victor Picheny; Matthieu Vignes (Stat. Comput., 2018)

$ mathcal{X}$-Armed Bandits: Optimizing Quantiles, CVaR and Other Risks. - Léonard Torossian; Aurélien Garivier; Victor Picheny (ACML, 2019)

X-Armed Bandits: Optimizing Quantiles and Other Risks. - Léonard Torossian; Aurélien Garivier; Victor Picheny (CoRR, 2019)

Modeling and Optimization with Gaussian Processes in Reduced Eigenbases - Extended Version. - David Gaudrie; Rodolphe Le Riche; Victor Picheny; Benoit Enaux; Vincent Herbert (CoRR, 2019)

Ordinal Bayesian Optimisation. - Victor Picheny; Sattar Vakili; Artem Artemev (CoRR, 2019)

A Bayesian optimization approach to find Nash equilibria. - Victor Picheny; Mickaël Binois; Abderrahmane Habbal (J. Glob. Optim., 2019)

Interpretable sparse SIR for functional data. - Victor Picheny; Rémi Servien; Nathalie Villa-Vialaneix (Stat. Comput., 2019)

Automatic Tuning of Stochastic Gradient Descent with Bayesian Optimisation. - Victor Picheny; Vincent Dutordoir; Artem Artemev; Nicolas Durrande (ECML/PKDD (3), 2020)

Targeting solutions in Bayesian multi-objective optimization: sequential and batch versions. - David Gaudrie; Rodolphe Le Riche; Victor Picheny; Benoit Enaux; Vincent Herbert (Ann. Math. Artif. Intell., 2020)

Bayesian Quantile and Expectile Optimisation. - Léonard Torossian; Victor Picheny; Nicolas Durrande (CoRR, 2020)

Regret Bounds for Noise-Free Bayesian Optimization. - Sattar Vakili; Victor Picheny; Nicolas Durrande (CoRR, 2020)

Gaussian process optimization with failures: classification and convergence proof. - François Bachoc; Céline Helbert; Victor Picheny (J. Glob. Optim., 2020)

The Kalai-Smorodinsky solution for many-objective Bayesian optimization. - Mickaël Binois; Victor Picheny; Patrick Taillandier; Abderrahmane Habbal (J. Mach. Learn. Res., 2020)

A review on quantile regression for stochastic computer experiments. - Léonard Torossian; Victor Picheny; Robert Faivre; Aurélien Garivier (Reliab. Eng. Syst. Saf., 2020)

On Information Gain and Regret Bounds in Gaussian Process Bandits. - Sattar Vakili; Kia Khezeli; Victor Picheny (AISTATS, 2021)

Scalable Thompson Sampling using Sparse Gaussian Process Models. - Sattar Vakili; Henry B. Moss; Artem Artemev; Vincent Dutordoir; Victor Picheny (NeurIPS, 2021)

Bayesian quantile and expectile optimisation. - Victor Picheny; Henry B. Moss; Léeonard Torossian; Nicolas Durrande (UAI, 2022)

Information-theoretic Inducing Point Placement for High-throughput Bayesian Optimisation. - Henry B. Moss; Sebastian W. Ober; Victor Picheny (CoRR, 2022)

A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design. - Andrei Paleyes; Henry B. Moss; Victor Picheny; Piotr Zulawski; Felix Newman (CoRR, 2022)

Fantasizing with Dual GPs in Bayesian Optimization and Active Learning. - Paul E. Chang; Prakhar Verma; S. T. John; Victor Picheny; Henry B. Moss; Arno Solin (CoRR, 2022)

Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation. - Henry B. Moss; Sebastian W. Ober; Victor Picheny (AISTATS, 2023)

Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes. - Louis C. Tiao; Vincent Dutordoir; Victor Picheny (ICML, 2023)

Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow. - Victor Picheny; Joel Berkeley; Henry B. Moss; Hrvoje Stojic; Uri Granta; Sebastian W. Ober; Artem Artemev; Khurram Ghani; Alexander Goodall; Andrei Paleyes; Sattar Vakili; Sergio Pascual-Diaz; et al. (CoRR, 2023)

A Game Theoretic Perspective on Bayesian Many-Objective Optimization. - Mickaël Binois; Abderrahmane Habbal; Victor Picheny (Many-Criteria Optimization and Decision Analysis, 2023)

TREGO: a trust-region framework for efficient global optimization. - Youssef Diouane; Victor Picheny; Rodolphe Le Riche; Alexandre Scotto Di Perrotolo (J. Glob. Optim., 2023)