activity
20182021
most citedShapes enhancing the propulsion of multiflagellated helical microswimmers

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cond-mat.soft20211 cited

Shapes enhancing the propulsion of multiflagellated helical microswimmers

Luca Berti, Mickaël Binois, François Alouges +3

In this paper we are interested in optimizing the shape of multi-flagellated helical microswimmers. Mimicking the propagation of helical waves along the flagella, they self-propel…

stat.ML2019

Sequential Learning of Active Subspaces

Nathan Wycoff, Mickael Binois, Stefan M. Wild

In recent years, active subspace methods (ASMs) have become a popular means of performing subspace sensitivity analysis on black-box functions. Naively applied, however, ASMs requi…

math.OC2019

The Kalai-Smorodinski solution for many-objective Bayesian optimization

Mickaël Binois, Victor Picheny, Patrick Taillandier +1

An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations…

stat.ME2018

On-site surrogates for large-scale calibration

Jiangeng Huang, Robert B. Gramacy, Mickael Binois +1

Motivated by a computer model calibration problem from the oil and gas industry, involving the design of a honeycomb seal, we develop a new Bayesian methodology to cope with limita…

stat.ML2018

Evaluating Gaussian Process Metamodels and Sequential Designs for Noisy Level Set Estimation

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. To efficiently reconstruct the level set, we investigate Gaussian…