no code implementations • 6 Feb 2024 • Mickael Binois, Victor Picheny
Gaussian processes are a widely embraced technique for regression and classification due to their good prediction accuracy, analytical tractability and built-in capabilities for uncertainty quantification.
no code implementations • 5 Jan 2024 • Khadija Musayeva, Mickael Binois
This paper proposes several approaches as baselines to compute a shared active subspace for multivariate vector-valued functions.
1 code implementation • 6 May 2023 • Arindam Fadikar, Mickael Binois, Nicholson Collier, Abby Stevens, Kok Ben Toh, Jonathan Ozik
Epidemiological models must be calibrated to ground truth for downstream tasks such as producing forward projections or running what-if scenarios.
no code implementations • 18 Oct 2021 • Mickael Binois, Nicholson Collier, Jonathan Ozik
One way to reduce the time of conducting optimization studies is to evaluate designs in parallel rather than just one-at-a-time.
no code implementations • 26 Jul 2019 • Nathan Wycoff, Mickael Binois, Stefan M. Wild
In such cases, often a surrogate model is employed, on which finite differencing is performed.
no code implementations • 18 Jul 2018 • Xiong Lyu, Mickael Binois, Michael Ludkovski
We consider the problem of learning the level set for which a noisy black-box function exceeds a given threshold.
no code implementations • 8 Nov 2016 • Victor Picheny, Mickael Binois, Abderrahmane Habbal
Game theory finds nowadays a broad range of applications in engineering and machine learning.