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I’m interested in developing interpretable machine learning models which complement human expertise, rather than attempt to replace it. For a high-level overview on some recent work, here’s a video of a talk I gave at the PROBPROG conference in Boston in September, 2018.
Previously I was a Turing research fellow based at the Alan Turing Institute; before that I was a DPhil student at University of Oxford, working with Frank Wood. My thesis focused on sequential Monte Carlo methods, and their application to general-purpose inference in probabilistic programs. A cliff-notes version is available as this short talk from back when I had long hair.
Previously I was a Turing research fellow based at the Alan Turing Institute; before that I was a DPhil student at University of Oxford, working with Frank Wood. My thesis focused on sequential Monte Carlo methods, and their application to general-purpose inference in probabilistic programs. A cliff-notes version is available as this short talk from back when I had long hair.
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crossref(2023)
CoRR (2023)
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crossref(2022)
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Kay Spiess,Timothy Fulton, Seogwon Hwang,Kane Toh,Dillan Saunders,Brooks Paige,Benjamin Steventon,Berta Verd
biorxiv(2022)
arxiv(2022)
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