Approximate Bayesian Computation Professors in Global

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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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Mohammad Salavatipour
University of Alberta Canada
approximation algorithms
hardness approximation
probabilistic randomized algorithms
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Johan Kwisthout
Radboud University Netherlands
approximate bayesian inference
bayesian networks
stochastic computing
computational complexity
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Debdeep Pati
University of Wisconsin–Madison United States of America
approximate bayesian methods
efficient bayesian computation
bayesian methods
bayesian graphical models
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James Beck
California Institute of Technology United States of America
computational bayesian statistics
bayesian updating
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Valen Johnson
Texas A&M University United States of America
bayesian variable selection
bayesian hypothesis testing
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Armin Iske
University of Hamburg Germany
numerical approximation
kernel-based approximation methods
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Monika Eisenmann
Lund University Sweden
numerical approximation
stochastic numerical analysis
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James Nichols
Australian National University Australia
approximation
high dimensional approximation theory
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Davoud Mirzaei
Uppsala University Sweden
scattered data approximation
function approximation
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Lisa Hellerstein
New York University Tandon School of Engineering United States of America
approximation algorithms
stochastic combinatorial optimization
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Paulo Serra
Vrije Universiteit Amsterdam Netherlands
bayesian non-parametrics
empirical bayes
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Marcus Bendtsen
Linköping University Sweden
bayesian statistics
quantitative estimation
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Ivan Kryven
Utrecht University Netherlands
random approximation algorithms
stochastic analysis
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Sandy Zabell
Northwestern University United States of America
bayesian statistics
mathematical probability
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Sandy Zabell
Northwestern University United States of America
bayesian statistics
mathematical probability
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Yuki Shiraito
University of Michigan United States of America
bayesian statistical models
large-scale computational algorithms
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Yixin Wang
University of Michigan United States of America
bayesian statistics
probabilistic generative modeling
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Shuchi Chawla
University of Texas at Austin United States of America
approximation online algorithms
combinatorial stochastic optimization
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Christopher Umans
California Institute of Technology United States of America
hardness approximation
randomness computation
computational complexity
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Christopher Umans
California Institute of Technology United States of America
hardness approximation
randomness computation
computational complexity
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