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

1–5 Sept 2025
ETH Zurich
Europe/Zurich timezone
  • 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 Tran Nhan

Dr
Fermi National Accelerator Laboratory, Batavia, IL, USA

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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