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Data Driven Density Functional Theory: A case for Physics Informed Learning

Oct 07, 2020
Peter Yatsyshin, Serafim Kalliadasis, Andrew B. Duncan


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Probabilistic Gradients for Fast Calibration of Differential Equation Models

Sep 03, 2020
Jon Cockayne, Andrew B. Duncan


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A Kernel Two-Sample Test for Functional Data

Aug 25, 2020
George Wynne, Andrew B. Duncan


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Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization

Jun 12, 2020
Shijing Si, Chris. J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol

* 24 pages, 7 figures 

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Minimum Stein Discrepancy Estimators

Jun 19, 2019
Alessandro Barp, Francois-Xavier Briol, Andrew B. Duncan, Mark Girolami, Lester Mackey


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Statistical Inference for Generative Models with Maximum Mean Discrepancy

Jun 13, 2019
Francois-Xavier Briol, Alessandro Barp, Andrew B. Duncan, Mark Girolami


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Measuring Sample Quality with Diffusions

Feb 21, 2018
Jackson Gorham, Andrew B. Duncan, Sebastian J. Vollmer, Lester Mackey


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