Bayesian Model Optimization Professors in Global

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Kalyanmoy Deb
Michigan State University United States of America
computational optimization
meta-modeling optimization
multi-objective optimization
evolutionary multi-objective optimization
hybrid optimization algorithms
process optimization
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Yanan Fan
University of New South Wales Australia
bayesian computation
bayesian inference
approximate bayesian computation
bayesian nonparametrics
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Debdeep Pati
University of Wisconsin–Madison United States of America
bayesian graphical models
bayesian methods
efficient bayesian computation
approximate bayesian methods
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Sharmistha Guha
Texas A&M University United States of America
bayesian high dimensional regression
bayesian object-oriented regression
bayesian causal inference
bayesian nonparametric mixture models
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Albert Berahas
University of Michigan United States of America
machine learning optimization
stochastic optimization
nonlinear optimization
constrained optimization
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Vijaya Raghavendra Bollapragada
University of Texas at Austin United States of America
stochastic optimization
optimization algorithms
nonlinear optimization
constrained optimization
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Juergen Branke
Warwick Business School United Kingdom
bayesian optimization
simulation-based optimization
multi-objective optimization
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Mayank Chadha
University of California, San Diego United States of America
bayesian optimization
bayesian decision theory
geometrically exact modeling
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Umberto Picchini
Chalmers University of Technology Sweden
bayesian computational methods
approximate bayesian computation
stochastic modelling
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Trevor Campbell
University of British Columbia Canada
bayesian inference
bayesian theory
bayesian nonparametrics
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Umberto Picchini
University of Gothenburg Sweden
bayesian computational methods
approximate bayesian computation
stochastic modelling
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Cynthia Vinzant
University of Washington United States of America
mathematical optimization
combinatorial optimization
linear optimization
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Robin Ryder
Imperial College London United Kingdom
bayesian computational statistics
approximate bayesian computation
stochastic modelling
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Ann-brith Strömberg
University of Gothenburg Sweden
mathematical optimization
simulation-based optimization
multi-objective optimization
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Xenia Miscouridou
Imperial College London United Kingdom
bayesian statistical machine learning
bayesian nonparametrics
stochastic process modeling
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Sebastian Denzler
Friedrich-Alexander-Universität Erlangen-Nürnberg Germany
robust bayesian optimization
optimization
distributionally robust optimization
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Ruth Misener
Imperial College London United Kingdom
optimization models
computational optimization
data-driven optimization
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Michael Patriksson
University of Gothenburg Sweden
mathematical optimization
combinatorial optimization
nonlinear optimization
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Navish Kumar
University of Basel Switzerland
bayesian inference
riemannian optimization
optimization
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Andrew Mccluskey
University of Bristol United Kingdom
bayesian analysis
mathematical modeling
statistical modeling
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Shixuan Zhang
Texas A&M University United States of America
stochastic optimization
polynomial optimization
integer optimization
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