Results 41 to 50 of about 289,279 (277)

Pseudo-Bayesian Optimization

, 2023
Bayesian Optimization is a popular approach for optimizing expensive black-box functions. Its key idea is to use a surrogate model to approximate the objective and, importantly, quantify the associated uncertainty that allows a sequential search of query points that balance exploitation-exploration.
Chen, Haoxian, Lam, Henry
openaire   +2 more sources

MIOpt: optimization framework for backward problems on the basis of the concept of materials integration

Science and Technology of Advanced Materials: Methods, 2023
In materials design, it is very difficult to accurately design forward problems owing to the variety of scales and phenomena to be considered and the increasing number of input and output variables.
Satoshi Minamoto, Koyo Daimaru, Masahiko Demura   +2 more
doaj   +1 more source

BayesOpt: A Bayesian Optimization Library for Nonlinear Optimization, Experimental Design and Bandits [PDF]

, 2014
BayesOpt is a library with state-of-the-art Bayesian optimization methods to solve nonlinear optimization, stochastic bandits or sequential experimental design problems.
Martinez-Cantin, Ruben
core   +1 more source

Global optimization of complex optical structures using Baysian optimization based on Gaussian processes

, 2017
Numerical simulation of complex optical structures enables their optimization with respect to specific objectives. Often, optimization is done by multiple successive parameter scans, which are time consuming and computationally expensive.
Burger, S., Rockstuhl, C., Santiago, X. Garcia, Schneider, P. -I.   +3 more
core   +1 more source

Bayesian $T$-optimal discriminating designs

The Annals of Statistics, 2015
The problem of constructing Bayesian optimal discriminating designs for a class of regression models with respect to the T-optimality criterion introduced by Atkinson and Fedorov (1975a) is considered. It is demonstrated that the discretization of the integral with respect to the prior distribution leads to locally T-optimal discriminating design ...
Dette, Holger, Melas, Viatcheslav B., Guchenko, Roman   +2 more
openaire   +6 more sources

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Development of graphical user interface for design of experiments via Gaussian process regression and its case study

Science and Technology of Advanced Materials: Methods
Bayesian optimization, coupled with Gaussian process regression and acquisition functions, has proven to be a powerful tool in the field of experimental design.
Yoshiki Hasukawa, Mikael Kuwahara, Lauren Takahashi, Keisuke Takahashi   +3 more
doaj   +1 more source

HAD-BO: A history-aware dynamic Bayesian optimization strategy and its applications in laser-driven plasma high-harmonic generation [PDF]

AIP Advances
An enhanced Bayesian optimization method, named History-Aware Dynamic Bayesian Optimization (HAD-BO), is proposed and applied to optimize the ellipticity in laser-driven plasma surface high-harmonic generation (SHHG).
Ziwei Wang, Chenfei Liao, Sergey Rykovanov, Lili Fan, Jingwei Wang   +4 more
doaj   +1 more source

Trajectories of Physical Function in Canadian Children with Juvenile Idiopathic Arthritis

Arthritis Care &Research, Accepted Article.
Objectives We describe trajectories of physical function in children newly diagnosed with juvenile idiopathic arthritis (JIA) and identify trajectories with persisting functional impairments and associated baseline characteristics. Methods We included patients enrolled in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry ...
Clare Cunningham, Meghan McPherson, Lillian Lim, Roberta A. Berard, Matthew Berkowitz, Jean‐Philippe Proulx‐Gauthier, Brian M. Feldman, Nicole Johnson, Dax G. Rumsey, Heinrike Schmeling, Lori B. Tucker, Thomas Loughin, Kristin M. Houghton, Jaime Guzman, The CAPRI Registry Investigators   +14 more
wiley   +1 more source

A Bayesian optimization approach for reliability-based design of prestressed concrete structures

Data-Centric Engineering
This paper presents a reliability-constrained Bayesian optimization framework for structural design under uncertainty, addressing challenges in stochastic optimization where the objectives and constraints are defined implicitly by potentially expensive ...
James Whiteley, Jurgen Becque
doaj   +1 more source