• Compact style
  • Indico style
  • Indico style - inline minutes
  • Indico style - numbered
  • Indico style - numbered + minutes
  • Indico Weeks View

Choose timezone

Your profile timezone:
Use timezone based on:
Login

Fast Machine Learning for Science Workshop 2022

3–6 Oct 2022
Southern Methodist University
America/Chicago timezone
  • Overview
  • Call for Abstracts
    • Timetable
    • Contribution List
    • Registration
    • Book of Abstracts
    • Participant List
    • Past workshops
    • Code of Conduct
    • Cultural/Tourist Activities in Dallas

    Details for Nhan Tran

    Fermi National Accelerator Lab. (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)
    • Quantized Distilled Autoencoder Model on FPGA for Real-Time Crystal Structure Detection in 4D Scanning Transmission Electron Microscopy
    • CryoAI – Prototyping cryogenic chips for machine learning at 22nm
    • In-Pixel AI: From Algorithm to Accelerator
    • Exploring FPGA in-storage computing for Supernova Burst detection in LArTPCs
    • Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks
    • Neural network accelerator for quantum control
    • 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
    • Semi-supervised Graph Neural Networks for Pileup Noise Removal
    CERN
    Powered by Indico v3.3.9-pre
    • Help
    • Contact
    • Terms and conditions
    • URL Shortener
    • Privacy