Results 51 to 60 of about 56,129 (265)

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

Surrogate modeling of waveform response using singular value decomposition and Bayesian optimization

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2021
In the early stage of vehicle development, it is required to implement a target cascading study by solving inverse problems. However, simulation costs of vehicle dynamics to predict transient responses and frequency responses make the target cascading ...
Kohei SHINTANI, Takao FUJIMOTO, Masaaki OKAMOTO, Atsuji ABE, Yasushi YAMAMOTO   +4 more
doaj   +1 more source

Bayesian Optimization with Gradients

CoRR, 2017
Bayesian optimization has been successful at global optimization of expensive-to-evaluate multimodal objective functions. However, unlike most optimization methods, Bayesian optimization typically does not use derivative information. In this paper we show how Bayesian optimization can exploit derivative information to decrease the number of objective ...
Jian Wu, Matthias Poloczek, Andrew Gordon Wilson, Peter I. Frazier   +3 more
openaire   +3 more sources

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi, Giorgio Ricciardiello Mejia, Andre Metzger, Kang Hyun Ryu, Salonee Marwaha, Eva Grzegorczyk, Li Zhou, Eliana Jacobs, Boris Gilyadov, Claudia Kunney, Liqhwa Ncube, Ankit Parekh, Emmanuel Mignot, Fanny M. Elahi, Joseph Winer, Kathleen Poston, Andreas Brink‐Kjaer, Emmanuel H. During   +17 more
wiley   +1 more source

Bayesian optimization algorithms for accelerator physics

Physical Review Accelerators and Beams
Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design and model calibration in simulations.
Ryan Roussel, Auralee L. Edelen, Tobias Boltz, Dylan Kennedy, Zhe Zhang, Fuhao Ji, Xiaobiao Huang, Daniel Ratner, Andrea Santamaria Garcia, Chenran Xu, Jan Kaiser, Angel Ferran Pousa, Annika Eichler, Jannis O. Lübsen, Natalie M. Isenberg, Yuan Gao, Nikita Kuklev, Jose Martinez, Brahim Mustapha, Verena Kain, Christopher Mayes, Weijian Lin, Simone Maria Liuzzo, Jason St. John, Matthew J. V. Streeter, Remi Lehe, Willie Neiswanger   +26 more
doaj   +1 more source

Real-time load forecasting model for the smart grid using bayesian optimized CNN-BiLSTM

Frontiers in Energy Research, 2023
A smart grid is a new type of power system based on modern information technology, which utilises advanced communication, computing and control technologies and employs advanced sensors, measurement, communication and control devices that can monitor the
Daohua Zhang, Daohua Zhang, Xinxin Jin, Piao Shi, XinYing Chew   +4 more
doaj   +1 more source

Optimal Bayesian Randomization

Journal of the Royal Statistical Society Series B: Statistical Methodology, 1997
Summary Randomization is a puzzle for Bayesians. The intuitive need for randomization is clear, but there is a standard result that Bayesians need not randomize. In this paper we propose a model in which randomization is a strictly optimal procedure.
Berry, Scott M., Kadane, Joseph B.
openaire   +2 more sources

Trajectories of Physical Function in Canadian Children With Juvenile Idiopathic Arthritis

Arthritis Care &Research, EarlyView.
Objective 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, for the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry Investigators, David A. Cabral, Gaëlle Chédeville, Ciarán M. Duffy, Kerstin Gerhold, Jaime Guzman, Linda Hiraki, Adam M. Huber, Heinrike Schmeling, Natalie J. Shiff, Lori B. Tucker, Julie Barsalou, Daniah Basodan, Michelle Batthish, Roberta A. Berard, Nicholas Blanchette, Gilles Boire, Roxana Bolaria, Alessandra Bruns, David A. Cabral, Sarah Campillo, Tania Cellucci, Mercedes Chan, Gaëlle Chédeville, Amieleena Chhabra, Julie Couture, Paul Dancey, Jean‐Jacques De Bruycker, Erkan Demirkaya, Muhammed Dhalla, Ciarán M. Duffy, Talal El Tal, Tommy Gerschman, Jaime Guzman, Liane Heale, Julie Herrington, Kristin M. Houghton, Adan M. Huber, Andrea Human, Nicole Johnson, Roman Jurencak, Bianca Lang, Claire LeBlanc, Lillian Lim, Lily S. H. Lim, Nadia Luca, Jeanine McColl, Tara McGrath, Tamara McMillan, Megan McPherson, Paivi Miettunen, Kimberly Morishita, Honyan Ng, Jonathan Park, Jean‐Philippe Proulx‐Gauthier, Johannes Roth, Evelyn Rozenblyum, Dax G. Rumsey, Heinrike Schmeling, Rosie Scuccimarri, Gordon Soon, Rebeka Stevenson, Elizabeth Stringer, Herman Tam, Lori B. Tucker, Marinka Twilt, Ruud H. J. Verstegen, Karen Watanabe Duffy   +81 more
wiley   +1 more source

The impact of Bayesian optimization on feature selection

Scientific Reports
Feature selection is an indispensable step for the analysis of high-dimensional molecular data. Despite its importance, consensus is lacking on how to choose the most appropriate feature selection methods, especially when the performance of the feature ...
Kaixin Yang, Long Liu, Yalu Wen
doaj   +1 more source

Application of Bayesian optimized XGBoost in seismic interpretation of small-scale faults

Meitan xuebao, 2023
In order to further improve the identification accuracy of small-scale faults in seismic interpretation, Bayesian optimized extreme gradient boosting (XGBoost) model was constructed to recognize small-scale faults across coalbeds using reduced seismic ...
Changwei DING, Xin WANG, Tongjun CHEN, Ting YU   +3 more
doaj   +1 more source