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Joint SSA Canberra Meeting + RLadies Meeting - 28 May

  • 13 May 2019 8:08 AM
    Message # 7337082
    Francis Hui (Administrator)

    Dear SSA Canberra and RLadies et al.,

    Please note we are now back on a Tuesday [Yay!], although the location is different [Sorry! Access and nearby parking to the Hanna Neumann building can be found at Where is the Hanna Neumann (MSI) building? and ANU parking]

    It is also somewhat of a hands-on session, so BYO laptops if you like. 

    Date: Tuesday 28 May 


    5.20pm Refreshments in Foyer, Ground level, Building 145 (Where is the Hanna Neumann (MSI) building?).

    6.00pm Presentation in Room 1.33, Building 145  

    7.00pm After the talk, there will be a dinner at China Plate, Kambri precinct ANU (Restaurant; noting this links to the one in Kingston; Map for location, which is relatively close to the Hanna Neumann building).

    Please RSVP SSA Canberra or reply to this email directly by 27 May if you would like to attend the dinner. 

    Speaker: Andrew Zammit Mangion, University of Wollongong

    Topic: Geostatistics in the fast lane using R-TensorFlow and GPUs


    Geostatistics plays a key role in the analysis and prediction of spatial and spatio-temporal phenomena. Spatial/spatio-temporal model fitting generally involves multiple matrix operations that can be slow to execute on a CPU. RStudio's interface to TensorFlow provides an ideal vehicle for doing spatial model fitting on a GPU in a fraction of the time needed by a CPU.

    I will first briefly talk about Google's TensorFlow and the associated R interface. I will then derive the maximum likelihood estimator for the parameters in a simple spatial model and implement maximum-likelihood estimation in R. Finally, I will show how to implement the same fitting procedure using Google's TensorFlow and illustrate the speed improvement when using a GPU. Attendees are invited to bring their own laptop with R and TensorFlow installed (see


    Andrew Zammit Mangion is Senior Lecturer and DECRA Research Fellow in the National Institute for Applied Statistics Research Australia (NIASRA), University of Wollongong, Australia. He is a co-author of two books and he has published over 20 peer-reviewed articles in the field of spatial and spatio-temporal statistics. He is also the author of a number of related R packages available on CRAN, including EFDR, FRK, and IDE. In 2013, Andrew was awarded a US National Academy of Sciences prize for his work on the modelling and prediction of armed conflicts.

    Website link:

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