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C. Herwig, An ML Control System for the Fermilab Booster, BIDS Machine Learning and Science Forum, April 2021, abstract
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P. Harris, Quick and Quirk with Quarks, IAIFI Colloquium Online, March 2021, video
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P. Harris, Scientific Applications of FPGAs at the LHC, ISFPGA 2021 (keynote), abstract
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J. Duarte, AI at the Edge of Particle Physics, video
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J. Duarte, hls4ml: An open-source codesign workflow to empower scientific low-power machine learning devices, tinyML Research Symposium 2021, video
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D. Rankin, FPGAs-as-a-Service Toolkit (FaaST), Heterogeneous High-Performance Reconfigurable Computing Workshop at Supercomputing 2020, slides
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P. Harris, ML Acceleration with Heterogeneous Computing for Big Data Physics Experiments, Heterogeneous High Performance Computing Workshop at Supercomputing 2019, slides
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K. Pedro, FPGA-accelerated machine learning inference as a service for particle physics computing, CHEP 2019, slides
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J. Duarte, Machine Learning on FPGAs for low latency and high throughput inference, eScience 2019, slides
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M. Liu, FPGA-accelerated machine learning inference as a solution for particle physics computing challenges, PASC 2019, slides
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J. Ngadiuba, hls4ml: deploying deep learning on FPGAs for trigger and data acquisition, ACAT 2019, slides
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J. Duarte, FPGA-accelerated machine learning inference for particle physics computing challenges, CTD 2019, slides
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J. Duarte, hls4ml: deploying deep learning on FPGAs for L1 trigger and data acquisition, TWEPP 2018, slides
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J. Ngadiuba, Synthesizing machine learning algorithms on FPGAs, CHEP 2018, slides
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N. Tran, Neural networks in FPGAs for trigger and DAQ, CTD 2018, slides