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DANCE Machine Learning Workshop 2020

Aug 3 – 7, 2020
US/Pacific timezone

Organizers

Contribution List

35 / 35
15. Getting Started with Machine Learning
Scott Kravitz (Lawrence Berkeley National Lab)
8/3/20, 8:00 AM

https://github.com/swkravitz/dance-ml-2020-tutorial
35. Processing of Graph-structured Data: An Introduction
Waheed Bajwa (Rutgers), Venkat Roy
8/3/20, 10:30 AM
48. Introduction to DANCE-ML and Workshop
Christopher Tunnell (Rice), Scott Kravitz (Lawrence Berkeley National Lab)
8/4/20, 8:00 AM
11. A readily-interpretable fully-convolutional autoencoder-like model for unlabelled waveform analysis
Ben Krikler (Bristol)
8/4/20, 8:15 AM
36. PMT waveform analysis in neutrino experiments
Dacheng Xu
8/4/20, 8:45 AM
12. Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
FREDERIC POITEVIN (LCLS, SLAC), Nina Miolane
8/4/20, 9:20 AM
17. LUX Summary
Scott Kravitz (Lawrence Berkeley National Lab)
8/4/20, 9:50 AM
37. Anomaly finding in the LZ dark matter experiment
Chami Amarasinghe (University of Michigan)
8/4/20, 10:10 AM
38. Room 1: Anomaly finding - applications and limitations
8/4/20, 11:00 AM
39. Room 2: How to design + when to apply generative models
8/4/20, 11:00 AM
19. Holistic Machine Learning Approach to Particle-Flow Reconstruction in Imaging Neutrino Detectors
Francois Drielsma, Francois Drielsma (SLAC)
8/5/20, 8:15 AM
20. Machine Learning at the Edge: Intelligent Data Triage in Real Time
Prof. Audrey Corbeil Therrien (Université de Sherbrooke), Ryan Coffee
8/5/20, 8:45 AM
49. Signal corrections of XENON1T Dark Matter detector
Tianyu Zhu (Columbia University)
8/5/20, 9:25 AM
50. Graph Neural Network for Position Reconstruction
Shixiao Liang (Rice University)
8/5/20, 9:35 AM
51. Convolutional neural network for S2 position reconstruction
Andrii Terliuk (MPIK, Heidelberg / Heidelberg University)
8/5/20, 9:45 AM
22. Machine Learning at SuperCDMS
To Chin Yu
8/5/20, 9:55 AM
23. Energy Reconstruction with Variational Autoencoders in SuperCDMS
Ashley Li (University of British Columbia)
8/5/20, 10:15 AM
41. Room 1: Snowmass planning (cross-collaboration LOI)
8/5/20, 11:00 AM
42. Room 2: Position and energy reconstruction
8/5/20, 11:00 AM
24. Mapping Machine-Learned Physics into a Human-Readable Space
Daniel Whiteson
8/6/20, 8:15 AM
26. PandaX-III, Investigation of possible features for the classification of signal and background with CNN
Shangning Xia, Shaobo Wang, Suizhi Huang
8/6/20, 8:45 AM
25. Machine learning for Neutrinoless Double Beta Decay in NEXT
Corey Adams (Argonne National Laboratory)
8/6/20, 9:05 AM
28. EXO Summary
Igor Ostrovskiy
8/6/20, 9:40 AM
27. Towards Deep Neural Network Analysis of Xe137 Decays to the Excited state of Cs137 in EXO-200 Data
Seth Thibado (University of Massechusetts)
8/6/20, 10:00 AM
29. Simulating scintillation signals in EXO-200 with GANs
Shaolei Li (University of Illinois at Urbana-Champaign)
8/6/20, 10:10 AM
44. Room 1: Ensuring robustness to systematics
8/6/20, 11:00 AM
45. Room 2: Quantifying uncertainties in inference
8/6/20, 11:00 AM
30. Measurements using all available information with OmniFold
Benjamin Nachman
8/7/20, 8:15 AM
31. Lessons from Industry
Manuel Weber (Descartes Labs)
8/7/20, 8:45 AM
32. Reconstruction and machine learning for water Cherenkov detectors
Nick Prouse (TRIUMF), Patrick de Perio
8/7/20, 9:30 AM
33. Summary of Machine Learning Applications for the COHERENT Collaboration
Peibo An (Duke University)
8/7/20, 9:50 AM
34. Physics-informed Gaussian Process for Real-time Tuning and Control of Particle Accelerators
Adi Hanuka (SLAC)
8/7/20, 10:10 AM
43. Discussion topic 3
46. Discussion topic 3
47. XENON Summary Talks
Andrii Terliuk (MPIK, Heidelberg / Heidelberg University), Shixiao Liang (Rice University), Tianyu Zhu (Columbia University)

1) Tianyu Zhu , "Signal corrections of XENON1T Dark Matter detector"
2) Shixiao Liang, "Graph Neural Network for Position Reconstruction"
3) Andrii Terliuk, "Convolutional neural network for S2 position
reconstruction"
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