Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Monash University
- University of Sheffield
- ;
- ETH Zurich
- Fraunhofer-Gesellschaft
- University of Glasgow
- University of New South Wales
- University of Toronto
- Forschungszentrum Jülich
- NIST
- Nature Careers
- Northeastern University
- Yale University
- BNU-HKBU United International College
- Columbia University
- Duke University
- Rice University
- SUNY Polytechnic Institute
- SciLifeLab
- Stony Brook University
- University of Bristol
- University of Cambridge
- University of Florida
- University of Houston Central Campus
- University of Lund
- University of North Carolina at Chapel Hill
- University of Nottingham
- Zintellect
- Aston University
- Baylor College of Medicine
- Binghamton University
- Career Education Corporation
- Case Western Reserve University
- Colorado Technical University
- Erasmus University Rotterdam
- Florida International University
- Freenome
- Grand Valley State University
- Harbin Engineering University
- Harvard University
- Imperial College London
- Indian Institute of Science Education & Research Thiruvananthapuram
- Institut Pasteur
- KINGS COLLEGE LONDON
- La Trobe University
- Leibniz
- Michigan State University
- Nanyang Technological University
- Oak Ridge National Laboratory
- Queensland University of Technology
- RMIT University
- SUNY University at Buffalo
- Simons Foundation/Flatiron Institute
- Technical University of Munich
- Texas A&M University
- The Ohio State University
- The University of Chicago
- University of Alabama, Tuscaloosa
- University of Delaware
- University of Hong Kong
- University of Nebraska–Lincoln
- University of North Carolina Wilmington
- University of Oklahoma
- University of Oregon
- University of Oslo
- University of Texas Health Science Center San Antonio
- University of Texas at Arlington
- University of Utah
- 58 more »
- « less
-
Field
-
Methods of balancing model complexity with goodness of fit include Akaike's information criterion (AIC), Schwarz's Bayesian information criterion (BIC), minimum description length (MDL) and minimum
-
characterization tools for closed loop experiment design, execution, and analysis, where experiment design is guided by active learning, Bayesian optimization, and similar methods. A key challenge is the integration
-
to, constraint programming, Bayesian methods, sparse kernel machines, graphical models, and latent variable analysis. Some examples of materials classes of interest for this project are photovoltaic
-
Bastian, C. C. (2018). Working memory updating and binding training: Bayesian evidence supporting the absence of transfer. Journal of Experimental Psychology: General, 147(6), 829-858. https://doi.org
-
. Among the approaches used will be the Bayesian information-theoretic Minimum Message Length (MML) principle (Wallace and Boulton, 1968; Wallace and Dowe, 1999a; Wallace, 2005) References: Wallace, C.S
-
, estimation, Bayesian paradigm. Benefits:https://www.suny.edu/media/suny/content-assets/documents/benefits/benefit-summaries/FTUUPbenefitsummary.pdf Requirements: Minimum Qualifications: Minimum qualification
-
, statistical significance, hypothesis testing, estimation, Bayesian paradigm. Benefits:https://www.suny.edu/media/suny/content-assets/documents/benefits/benefit-summaries/FTUUPbenefitsummary.pdf Requirements
-
of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K
-
used will the information-theoretic Bayesian minimum message length (MML) principle. Student cohort PhD, possibly Master’s (Minor Thesis) or Honours URLs/references Chen, Li and Gao, Jiti and Vahid
-
techniques for annotation, active learning (based on either deep learning or Bayesian learning), semi-supervised learning, transfer learning, imitation learning, etc., aiming to ensure the data and models