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Fast Machine Learning for Science Workshop 2022

3–6 Oct 2022
Southern Methodist University
America/Chicago timezone
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    Details for Javier Mauricio Duarte

    Univ. of California San Diego (US)

    Author in the following contributions

    • FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning
    • FKeras: A Fault Tolerance Library for DNNs
    • Next Generation Coprocessors as a service
    • Quantized ONNX (QONNX)
    • Resource Efficient and Low Latency GNN-based Particle Tracking on FPGA
    • Quantized Distilled Autoencoder Model on FPGA for Real-Time Crystal Structure Detection in 4D Scanning Transmission Electron Microscopy
    • Increasing the LHC Computational Power by integrating GPUs as a service
    • Design and first test results of a reconfigurable autoencoder on an ASIC for data compression at the HL-LHC
    • EMD Neural Network Loss for ECON-T ASIC Autoencoder
    CERN
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