ML-at-SLAC 1st Workshop

Tuesday 19 Feb 2019, 10:00 → 19:00 America/Los_Angeles

53-1-1350 Trinity (SLAC)

Kazuhiro Terao (SLAC), Daniel Ratner (SLAC)

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

10:00 → 10:55 Morning: Invited Talks 1

Convener: Daniel Ratner (SLAC)

10:00 Introduction

Speaker: Kazuhiro Terao (SLAC)

10:05 Deep Learning at the Particle Physics Energy Frontier

Speaker: Dr Michael Kagan (SLAC)

Deep Learning for Particle Physics Energy Frontier

10:15 HEP - Intensity Frontier: Deep Neural Networks for 2D/3D Particle Image Analysis

Speakers: Kazuhiro Terao (SLAC), Laura Domine (Stanford University)

2019_02_19_ML-at-SLAC-HEP-IF.pdf

10:25 HEP - Cosmic Frontier: Deep Generative Models for Astronomical Catalogs

Speaker: Dr Philip Marshall (SLAC)

LSST Catalog-Level Emulation and Detection

10:35 Stanford Galaxy Formation and Cosmology ML Research

Speakers: Sean McLaughlin (Stanford University), Warren Morningstar (Stanford University)

Stanford Galaxy Formation and Cosmology ML Research

10:45 Machine Learning for the Heavy Photon Search

Speakers: Dr Matthew Solt (SLAC), Dr Omar Moreno (SLAC)

MLatSLAC_solt.pdf

10:55 → 11:05 Morning caffeine recharge

11:05 → 12:00 Morning: Invited Talks 2

Convener: Kazuhiro Terao (SLAC)

11:05 Machine learning in computational surface chemistry

Speaker: Dr Johannes Voss (SLAC)

11:15 Improving Particle Accelerator Models with Machine Learning

Speaker: Dr Auralee Edelen (SLAC)

20190217_Accelerator_Models_Edelen.pdf

11:25 Bayesian optimization for FEL tuning: a step towards autonomous operation

Speaker: Dr Joseph Duris (SLAC)

Bayesian optimization for FEL tuning

11:35 Machine Learning based Analysis, Accelerator Directorate

Speaker: Dr Brendan O'Shea (SLAC)

MLatSLAC_DataAnalysis.key

MLatSLAC_DataAnalysis.key

MLatSLAC_DataAnalysis.pptx

11:50 ML Study: SPEAR3 BTS Injection Efficiency

Speaker: Faya Wang (SLAC)

SPEAR3_injeff_ML_Wang_5.pptx

12:00 → 13:00 Lunch break

13:00 → 14:10 Afternoon: Invited Talks 3

Convener: Kazuhiro Terao (SLAC)

13:00 CryoET of Cells

Speakers: Prof. Wah Chiu (SLAC), Yee Li (SLAC)

13:10 Machine Learning for Double Beta Decay with EXO-200

Speaker: Lisa Kaufman (SLAC)

ML_EXO200v3.pdf

13:20 Accelerating Discoveries by iterating machine learning with high throughput experiments and computations

Speaker: Dr Apurva Mehta (SLAC)

Apurva MLatSLACworkshopFeb2019.pptx

13:30 Data-driven discovery of plasma physics

Speaker: Dr Paulo Alves (SLAC)

13:40 Deploying ML In Hardware: FPGAs & ASICs

Speaker: Dr Ryan Herbst (SLAC)

SLAC ML Workshop 2019_02_18.pdf

13:50 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

14:00 Machine Learning in SFX and SPI

Speaker: Dr Chun Hong Yoon (SLAC)

MLatSLAC19.pdf

14:10 → 16:00 Poster presentation + caffeine break

Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)

14:10 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

16:00 → 17:00 Discussion

Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)

17:00 → 19:00 Booze

Conveners: Daniel Ratner (SLAC), Kazuhiro Terao (SLAC)