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ML-at-SLAC 1st Workshop

→ America/Los_Angeles
53-1-1350 Trinity (SLAC)

53-1-1350 Trinity

SLAC

2575 Sand Hill Rd. Menlo Park, CA 94025 Building 53 Zoom: https://stanford.zoom.us/j/8036931498
Kazuhiro Terao (SLAC), Daniel Ratner (SLAC)
Description

https://stanford.zoom.us/j/8036931498

Kazuhiro Terao
    • Morning: Invited Talks 1
      Convener: Daniel Ratner (SLAC)
    • 10:55
      Morning caffeine recharge
    • Morning: Invited Talks 2
      Convener: Kazuhiro Terao (SLAC)
    • 12:00
      Lunch break
    • Afternoon: Invited Talks 3
      Convener: Kazuhiro Terao (SLAC)
      • 12
        CryoET of Cells
        Speakers: Prof. Wah Chiu (SLAC), Yee Li (SLAC)
      • 13
        Machine Learning for Double Beta Decay with EXO-200
        Speaker: Lisa Kaufman (SLAC)
        ML_EXO200v3.pdf
      • 14
        Accelerating Discoveries by iterating machine learning with high throughput experiments and computations
        Speaker: Dr Apurva Mehta (SLAC)
        Apurva MLatSLACworkshopFeb2019.pptx
      • 15
        Data-driven discovery of plasma physics
        Speaker: Dr Paulo Alves (SLAC)
      • 16
        Deploying ML In Hardware: FPGAs & ASICs
        Speaker: Dr Ryan Herbst (SLAC)
        SLAC ML Workshop 2019_02_18.pdf
      • 17
        Machine Learning at the Edge : High velocity data inferencing
        Speakers: Audrey Therrien (SLAC), Omar Quijano (SLAC), Dr Ryan Coffee (SLAC)
        ML_at_the_edge_Coffee_Therrien_Quijano.pptx
      • 18
        Machine Learning in SFX and SPI
        Speaker: Dr Chun Hong Yoon (SLAC)
        MLatSLAC19.pdf
    • Poster presentation + caffeine break
      Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)
      • 19
        Awesome ML Posters

        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 CNNs
        Ultrafast Processing of Pixel Detector Data with Machine Learning
        SPEAR3 BTS Injection Efficiency
        Machine Learning to digest CookieBox Data
        Constrained BEEF-type Functionals for Catalysis
        Meta-GGA and hybrid Bayesian error estimation functionals
        Accelerating ab initio calculations using surrogate machine learning models
        Model Independent Analysis of Beam Centroid Data for LCLS
        Machine Learning In Hardware
        Applying Deep Neural Network Techniques For LArTPC Data Reconstruction
        Semi-Supervised Classification of Astronomical Time Series
        Power Prediction from Electron Phase with Vision-based Neural Network
        Peak finding for crystallography
        Gaussian Processes for Bayesian Deconvolution and Source Separation: Applications to XFEL Spectroscopy
        Machine Learning in Tapered Free Electron Laser: Power Optimization and Sideband Identification

        Speakers: 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)
        20190217_Accelerator_Models_Edelen_poster.pdf
        C_Emma_ML_at_SLAC_poster_FEb_2019.pdf
        Deploying ML In Hardware: FPGAs & ASICs
        jose.pdf
        Loukianov-poster-02-19-19.pdf
        MachineLearningCookieBoxData.pdf
        Monzani_Fermi_UnID.pdf
        oliveira.pdf
        ponanli.pdf
        Ultrafast Processing of 2D Detector Data with Machine Learning
        xiao.pdf
    • Discussion
      Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)
    • Booze
      Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)
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