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    Fast Machine Learning for Science Conference 2025
    Fast Machine Learning for Science Conference 2025

    Sep 1 – 5, 2025
    ETH Zurich
    Europe/Zurich timezone

    Event menu

    • Overview
    • Invited Speakers
    • Timetable
    • Contribution List
    • Book of Abstracts
    • Registration
    • How to become a Sponsor
    • Poster awards
    • Practical information
    • Conference photo

    Local organisers

    • fml-2025-organisers@cern.ch

    Details for Nhan Tran

    Fermi National Accelerator Lab. (US)

    Author in the following contributions

    • Towards Online Machine Learning in DUNE Data Acquisition
    • Towards a Self-Driving Trigger: Adaptive Response in Real Time
    • Super Neural Architecture Codesign Package (SNAC-Pack)
    • PrioriFI: Efficient Fault Injection for Edge Neural Networks
    • Smartpixels: Intelligent pixel detectors: Towards a radiation hard ASIC with on-chip machine learning in 28nm CMOS
    • Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing
    • MLCommons Science Benchmarks
    • wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation
    • State Space Models for Scientific Time Series Applications
    • Improving On-Chip Compression of High-Granularity Calorimeter Data with Conditional Autoencoders
    • Fast Adaptive Neural Control of Resonant Extraction at Fermilab
    CERN
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