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Developing a Series of AI Challenges for the United States Department of the Air Force


Jul 14, 2022
Vijay Gadepally, Gregory Angelides, Andrei Barbu, Andrew Bowne, Laura J. Brattain, Tamara Broderick, Armando Cabrera, Glenn Carl, Ronisha Carter, Miriam Cha, Emilie Cowen, Jesse Cummings, Bill Freeman, James Glass, Sam Goldberg, Mark Hamilton, Thomas Heldt, Kuan Wei Huang, Phillip Isola, Boris Katz, Jamie Koerner, Yen-Chen Lin, David Mayo, Kyle McAlpin, Taylor Perron, Jean Piou, Hrishikesh M. Rao, Hayley Reynolds, Kaira Samuel, Siddharth Samsi, Morgan Schmidt, Leslie Shing, Olga Simek, Brandon Swenson, Vivienne Sze, Jonathan Taylor, Paul Tylkin, Mark Veillette, Matthew L Weiss, Allan Wollaber, Sophia Yuditskaya, Jeremy Kepner


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Black-box Selective Inference via Bootstrapping


Mar 28, 2022
Sifan Liu, Jelena Markovic, Jonathan Taylor


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VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relighting


Jan 13, 2022
Feitong Tan, Sean Fanello, Abhimitra Meka, Sergio Orts-Escolano, Danhang Tang, Rohit Pandey, Jonathan Taylor, Ping Tan, Yinda Zhang


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Signal Enhancement for Magnetic Navigation Challenge Problem


Jul 23, 2020
Albert R. Gnadt, Joseph Belarge, Aaron Canciani, Lauren Conger, Joseph Curro, Alan Edelman, Peter Morales, Michael F. O'Keeffe, Jonathan Taylor, Christopher Rackauckas

* 21 pages, 4 figures. See https://github.com/MIT-AI-Accelerator/MagNav.jl for accompanying data and code 

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Deep Implicit Volume Compression


May 18, 2020
Danhang Tang, Saurabh Singh, Philip A. Chou, Christian Haene, Mingsong Dou, Sean Fanello, Jonathan Taylor, Philip Davidson, Onur G. Guleryuz, Yinda Zhang, Shahram Izadi, Andrea Tagliasacchi, Sofien Bouaziz, Cem Keskin

* Danhang Tang and Saurabh Singh have equal contribution 

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Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning


May 29, 2019
Rohit Pandey, Anastasia Tkach, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Ricardo Martin-Brualla, Andrea Tagliasacchi, George Papandreou, Philip Davidson, Cem Keskin, Shahram Izadi, Sean Fanello


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LookinGood: Enhancing Performance Capture with Real-time Neural Re-Rendering


Nov 12, 2018
Ricardo Martin-Brualla, Rohit Pandey, Shuoran Yang, Pavel Pidlypenskyi, Jonathan Taylor, Julien Valentin, Sameh Khamis, Philip Davidson, Anastasia Tkach, Peter Lincoln, Adarsh Kowdle, Christoph Rhemann, Dan B Goldman, Cem Keskin, Steve Seitz, Shahram Izadi, Sean Fanello

* The supplementary video is available at: http://youtu.be/Md3tdAKoLGU To be presented at SIGGRAPH Asia 2018 

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Why Adaptively Collected Data Have Negative Bias and How to Correct for It


Dec 30, 2017
Xinkun Nie, Xiaoying Tian, Jonathan Taylor, James Zou

* Accepted to the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018, Lanzarote, Spain 

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Summary - TerpreT: A Probabilistic Programming Language for Program Induction


Dec 02, 2016
Alexander L. Gaunt, Marc Brockschmidt, Rishabh Singh, Nate Kushman, Pushmeet Kohli, Jonathan Taylor, Daniel Tarlow

* 7 pages, 2 figures, 4 tables in 1st Workshop on Neural Abstract Machines & Program Induction (NAMPI), @NIPS 2016 

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High-dimensional regression adjustments in randomized experiments


Oct 27, 2016
Stefan Wager, Wenfei Du, Jonathan Taylor, Robert Tibshirani

* To appear in the Proceedings of the National Academy of Sciences. The present draft does not reflect final copyediting by the PNAS staff 

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