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DANCE Machine Learning Workshop 2020

3–7 Aug 2020

US/Pacific timezone

Organizers

Speaker List

Corey Adams (Argonne National Laboratory)
- Speaker at Machine learning for Neutrinoless Double Beta Decay in NEXT
Chami Amarasinghe (University of Michigan)
- Speaker at Anomaly finding in the LZ dark matter experiment
Peibo An (Duke University)
- Speaker at Summary of Machine Learning Applications for the COHERENT Collaboration
Waheed Bajwa (Rutgers)
- Speaker at Processing of Graph-structured Data: An Introduction
Ryan Coffee
- Speaker at Machine Learning at the Edge: Intelligent Data Triage in Real Time
Audrey Corbeil Therrien (Université de Sherbrooke)
- Speaker at Machine Learning at the Edge: Intelligent Data Triage in Real Time
Patrick de Perio
- Speaker at Reconstruction and machine learning for water Cherenkov detectors
Francois Drielsma
- Speaker at Holistic Machine Learning Approach to Particle-Flow Reconstruction in Imaging Neutrino Detectors
Francois Drielsma (SLAC)
- Speaker at Holistic Machine Learning Approach to Particle-Flow Reconstruction in Imaging Neutrino Detectors
Adi Hanuka
- Speaker at Physics-informed Gaussian Process for Real-time Tuning and Control of Particle Accelerators
Suizhi Huang
- Speaker at PandaX-III, Investigation of possible features for the classification of signal and background with CNN
Scott Kravitz (Lawrence Berkeley National Lab)
- Speaker at Getting Started with Machine Learning
- Speaker at LUX Summary
- Speaker at Introduction to DANCE-ML and Workshop
Ben Krikler (LZ)
- Speaker at A readily-interpretable fully-convolutional autoencoder-like model for unlabelled waveform analysis
Shaolei Li
- Speaker at Simulating scintillation signals in EXO-200 with GANs
Ashley Li (University of British Columbia)
- Speaker at Energy Reconstruction with Variational Autoencoders in SuperCDMS
Shixiao Liang (Rice University)
- Speaker at Graph Neural Network for Position Reconstruction
- Speaker at XENON Summary Talks
Nina Miolane
- Speaker at Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
Benjamin Nachman
- Speaker at Measurements using all available information with OmniFold
Igor Ostrovskiy
- Speaker at EXO Summary
FREDERIC POITEVIN (LCLS, SLAC)
- Speaker at Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
Nick Prouse (TRIUMF)
- Speaker at Reconstruction and machine learning for water Cherenkov detectors
Venkat Roy
- Speaker at Processing of Graph-structured Data: An Introduction
Andrii Terliuk (MPIK, Heidelberg / Heidelberg University)
- Speaker at Convolutional neural network for S2 position reconstruction
- Speaker at XENON Summary Talks
Seth Thibado (University of Massechusetts)
- Speaker at Towards Deep Neural Network Analysis of Xe137 Decays to the Excited state of Cs137 in EXO-200 Data
Christopher Tunnell (Rice)
- Speaker at Introduction to DANCE-ML and Workshop
Shaobo Wang
- Speaker at PandaX-III, Investigation of possible features for the classification of signal and background with CNN
Manuel Weber
- Speaker at Lessons from Industry
Daniel Whiteson
- Speaker at Mapping Machine-Learned Physics into a Human-Readable Space
Shangning Xia
- Speaker at PandaX-III, Investigation of possible features for the classification of signal and background with CNN
Dacheng Xu
- Speaker at PMT waveform analysis in neutrino experiments
To Chin Yu
- Speaker at Machine Learning at SuperCDMS
Tianyu Zhu (Columbia University)
- Speaker at Signal corrections of XENON1T Dark Matter detector
- Speaker at XENON Summary Talks

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