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FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs


Sep 26, 2022
Shehzeen Hussain, Nojan Sheybani, Paarth Neekhara, Xinqiao Zhang, Javier Duarte, Farinaz Koushanfar

* Accepted at ICCAD 2022 

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Data Science and Machine Learning in Education


Jul 19, 2022
Gabriele Benelli, Thomas Y. Chen, Javier Duarte, Matthew Feickert, Matthew Graham, Lindsey Gray, Dan Hackett, Phil Harris, Shih-Chieh Hsu, Gregor Kasieczka, Elham E. Khoda, Matthias Komm, Mia Liu, Mark S. Neubauer, Scarlet Norberg, Alexx Perloff, Marcel Rieger, Claire Savard, Kazuhiro Terao, Savannah Thais, Avik Roy, Jean-Roch Vlimant, Grigorios Chachamis

* Contribution to Snowmass 2021 

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FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning


Jul 16, 2022
Javier Duarte, Nhan Tran, Ben Hawks, Christian Herwig, Jules Muhizi, Shvetank Prakash, Vijay Janapa Reddi

* 9 pages, 4 figures, Contribution to 3rd Workshop on Benchmarking Machine Learning Workloads on Emerging Hardware (MLBench) at 5th Conference on Machine Learning and Systems (MLSys) 

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark


Jun 23, 2022
Hendrik Borras, Giuseppe Di Guglielmo, Javier Duarte, Nicolò Ghielmetti, Ben Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott

* 15 pages, 7 figures, Contribution to 3rd Workshop on Benchmarking Machine Learning Workloads on Emerging Hardware (MLBench) at 5th Conference on Machine Learning and Systems (MLSys) 

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QONNX: Representing Arbitrary-Precision Quantized Neural Networks


Jun 17, 2022
Alessandro Pappalardo, Yaman Umuroglu, Michaela Blott, Jovan Mitrevski, Ben Hawks, Nhan Tran, Vladimir Loncar, Sioni Summers, Hendrik Borras, Jules Muhizi, Matthew Trahms, Shih-Chieh Hsu, Scott Hauck, Javier Duarte

* 9 pages, 5 figures, Contribution to 4th Workshop on Accelerated Machine Learning (AccML) at HiPEAC 2022 Conference 

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Physics Community Needs, Tools, and Resources for Machine Learning


Mar 30, 2022
Philip Harris, Erik Katsavounidis, William Patrick McCormack, Dylan Rankin, Yongbin Feng, Abhijith Gandrakota, Christian Herwig, Burt Holzman, Kevin Pedro, Nhan Tran, Tingjun Yang, Jennifer Ngadiuba, Michael Coughlin, Scott Hauck, Shih-Chieh Hsu, Elham E Khoda, Deming Chen, Mark Neubauer, Javier Duarte, Georgia Karagiorgi, Mia Liu

* Contribution to Snowmass 2021, 33 pages, 5 figures 

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Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges


Mar 25, 2022
Savannah Thais, Paolo Calafiura, Grigorios Chachamis, Gage DeZoort, Javier Duarte, Sanmay Ganguly, Michael Kagan, Daniel Murnane, Mark S. Neubauer, Kazuhiro Terao

* contribution to Snowmass 2021 

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Particle-based Fast Jet Simulation at the LHC with Variational Autoencoders


Mar 01, 2022
Mary Touranakou, Nadezda Chernyavskaya, Javier Duarte, Dimitrios Gunopulos, Raghav Kansal, Breno Orzari, Maurizio Pierini, Thiago Tomei, Jean-Roch Vlimant

* 11 pages, 8 figures 

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Machine Learning for Particle Flow Reconstruction at CMS


Mar 01, 2022
Joosep Pata, Javier Duarte, Farouk Mokhtar, Eric Wulff, Jieun Yoo, Jean-Roch Vlimant, Maurizio Pierini, Maria Girone

* 12 pages, 6 figures. Presented at the ACAT 2021: 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Daejeon, Kr, 29 Nov - 3 Dec 2021 

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Graph Neural Networks for Charged Particle Tracking on FPGAs


Dec 03, 2021
Abdelrahman Elabd, Vesal Razavimaleki, Shi-Yu Huang, Javier Duarte, Markus Atkinson, Gage DeZoort, Peter Elmer, Jin-Xuan Hu, Shih-Chieh Hsu, Bo-Cheng Lai, Mark Neubauer, Isobel Ojalvo, Savannah Thais

* 26 pages, 17 figures, 1 table 

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