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ML-at-SLAC 1st Workshop

19 February 2019
SLAC
America/Los_Angeles timezone

Kazuhiro Terao

Contribution List

19 out of 19 displayed
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  1. 3. Introduction
    Kazuhiro Terao (SLAC)
    19/02/2019, 10:00
  2. 4. Deep Learning at the Particle Physics Energy Frontier
    Dr Michael Kagan (SLAC)
    19/02/2019, 10:05
  3. 5. HEP - Intensity Frontier: Deep Neural Networks for 2D/3D Particle Image Analysis
    Kazuhiro Terao (SLAC), Laura Domine (Stanford University)
    19/02/2019, 10:15
  4. 6. HEP - Cosmic Frontier: Deep Generative Models for Astronomical Catalogs
    Dr Philip Marshall (SLAC)
    19/02/2019, 10:25
  5. 7. Stanford Galaxy Formation and Cosmology ML Research
    Sean McLaughlin (Stanford University), Warren Morningstar (Stanford University)
    19/02/2019, 10:35
  6. 9. Machine Learning for the Heavy Photon Search
    Dr Matthew Solt (SLAC), Dr Omar Moreno (SLAC)
    19/02/2019, 10:45
  7. 16. Machine learning in computational surface chemistry
    Dr Johannes Voss (SLAC)
    19/02/2019, 11:05
  8. 10. Improving Particle Accelerator Models with Machine Learning
    Dr Auralee Edelen (SLAC)
    19/02/2019, 11:15
  9. 11. Bayesian optimization for FEL tuning: a step towards autonomous operation
    Dr Joseph Duris (SLAC)
    19/02/2019, 11:25
  10. 12. Machine Learning based Analysis, Accelerator Directorate
    Dr Brendan O'Shea (SLAC)
    19/02/2019, 11:35
  11. 13. ML Study: SPEAR3 BTS Injection Efficiency
    Faya Wang (SLAC)
    19/02/2019, 11:50
  12. 14. CryoET of Cells
    Prof. Wah Chiu (SLAC), Yee Li (SLAC)
    19/02/2019, 13:00
  13. 22. Machine Learning for Double Beta Decay with EXO-200
    Lisa Kaufman (SLAC)
    19/02/2019, 13:10
  14. 21. Accelerating Discoveries by iterating machine learning with high throughput experiments and computations
    Dr Apurva Mehta (SLAC)
    19/02/2019, 13:20
  15. 17. Data-driven discovery of plasma physics
    Dr Paulo Alves (SLAC)
    19/02/2019, 13:30
  16. 18. Deploying ML In Hardware: FPGAs & ASICs
    Dr Ryan Herbst (SLAC)
    19/02/2019, 13:40
  17. 19. Machine Learning at the Edge : High velocity data inferencing
    Audrey Therrien (SLAC), Omar Quijano (SLAC), Dr Ryan Coffee (SLAC)
    19/02/2019, 13:50
  18. 20. Machine Learning in SFX and SPI
    Dr Chun Hong Yoon (SLAC)
    19/02/2019, 14:00
  19. 23. Awesome ML Posters
    Anton Loukianov (SLAC), Audrey Therrien (SLAC), Dr Auralee Edelen (SLAC), Dr Chun Hong Yoon (SLAC), Claudio Emma (SLAC), Faya Wang (SLAC), Gabriel Blaj (SLAC), Henry van den Bedem (Stanford University), Ji Won Park (Stanford University), Jose Torres (Stanford University), Dr Joseph Duris (SLAC), Juhao Wu (SLAC), Kristopher Brown (Stanford University), Laura Domine (Stanford University), Dr Maria Elena Monzani (SLAC), Dr Paulo Alves (SLAC), Ponan Li (SLAC), Dr Ryan Herbst (SLAC), Saulo Oliveira (Stanford University), Sean McLaughlin (Stanford University), Sowmya Kamath (Stanford University), William Colocho (Stanford University), Xiao Zhang (Stanford), Xiaobiao Huang (SLAC), Xinyu Ren (SLAC), Yasheng Maimaiti (Stanford University)
    19/02/2019, 14:10

    Bayesian optimization of FEL pulse energy
    Data-driven discovery of plasma physics
    Machine Learning at the Heavy Photon Search Experiment
    A Statistical Approach to Recognizing Source Classes for Unassociated Sources in Fermi-LAT Catalogs
    Identify undetected galaxies with conventional and machine learning techniques
    Temporal Electric Field Reconstruction
    Bayesian Cosmological Inference with...

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