DANCE Machine Learning Workshop 2020

Contribution List

15. Getting Started with Machine Learning

Scott Kravitz (Lawrence Berkeley National Lab)

03/08/2020, 08:00

Tutorial

https://github.com/swkravitz/dance-ml-2020-tutorial

35. Processing of Graph-structured Data: An Introduction

Waheed Bajwa (Rutgers), Venkat Roy

03/08/2020, 10:30

48. Introduction to DANCE-ML and Workshop

Christopher Tunnell (Rice), Scott Kravitz (Lawrence Berkeley National Lab)

04/08/2020, 08:00

11. A readily-interpretable fully-convolutional autoencoder-like model for unlabelled waveform analysis

Ben Krikler (Bristol)

04/08/2020, 08:15

Unsupervised/semi-supervised learning

36. PMT waveform analysis in neutrino experiments

Dacheng Xu

04/08/2020, 08:45

Unsupervised/semi-supervised learning

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

04/08/2020, 09:20

Unsupervised/semi-supervised learning

17. LUX Summary

Scott Kravitz (Lawrence Berkeley National Lab)

04/08/2020, 09:50

Unsupervised/semi-supervised learning

37. Anomaly finding in the LZ dark matter experiment

Chami Amarasinghe (University of Michigan)

04/08/2020, 10:10

Unsupervised/semi-supervised learning

38. Room 1: Anomaly finding - applications and limitations

04/08/2020, 11:00

Unsupervised/semi-supervised learning

39. Room 2: How to design + when to apply generative models

04/08/2020, 11:00

Unsupervised/semi-supervised learning

19. Holistic Machine Learning Approach to Particle-Flow Reconstruction in Imaging Neutrino Detectors

Francois Drielsma, Francois Drielsma (SLAC)

05/08/2020, 08:15

Reconstruction and whitepaper

20. Machine Learning at the Edge: Intelligent Data Triage in Real Time

Prof. Audrey Corbeil Therrien (Université de Sherbrooke), Ryan Coffee

05/08/2020, 08:45

Reconstruction and whitepaper

49. Signal corrections of XENON1T Dark Matter detector

Tianyu Zhu (Columbia University)

05/08/2020, 09:25

Reconstruction and whitepaper

50. Graph Neural Network for Position Reconstruction

Shixiao Liang (Rice University)

05/08/2020, 09:35

Reconstruction and whitepaper

51. Convolutional neural network for S2 position reconstruction

Andrii Terliuk (MPIK, Heidelberg / Heidelberg University)

05/08/2020, 09:45

Reconstruction and whitepaper

22. Machine Learning at SuperCDMS

To Chin Yu

05/08/2020, 09:55

Reconstruction and whitepaper

23. Energy Reconstruction with Variational Autoencoders in SuperCDMS

Ashley Li (University of British Columbia)

05/08/2020, 10:15

Reconstruction and whitepaper

41. Room 1: Snowmass planning (cross-collaboration LOI)

05/08/2020, 11:00

Reconstruction and whitepaper

42. Room 2: Position and energy reconstruction

05/08/2020, 11:00

Reconstruction and whitepaper

24. Mapping Machine-Learned Physics into a Human-Readable Space

Daniel Whiteson

06/08/2020, 08:15

Interpretability and uncertainty estimation

26. PandaX-III, Investigation of possible features for the classification of signal and background with CNN

Shangning Xia, Shaobo Wang, Suizhi Huang

06/08/2020, 08:45

Interpretability and uncertainty estimation

25. Machine learning for Neutrinoless Double Beta Decay in NEXT

Corey Adams (Argonne National Laboratory)

06/08/2020, 09:05

Interpretability and uncertainty estimation

28. EXO Summary

Igor Ostrovskiy

06/08/2020, 09:40

Interpretability and uncertainty estimation

27. Towards Deep Neural Network Analysis of Xe137 Decays to the Excited state of Cs137 in EXO-200 Data

Seth Thibado (University of Massechusetts)

06/08/2020, 10:00

Interpretability and uncertainty estimation

29. Simulating scintillation signals in EXO-200 with GANs

Shaolei Li (University of Illinois at Urbana-Champaign)

06/08/2020, 10:10

Interpretability and uncertainty estimation

44. Room 1: Ensuring robustness to systematics

06/08/2020, 11:00

Interpretability and uncertainty estimation

45. Room 2: Quantifying uncertainties in inference

06/08/2020, 11:00

Interpretability and uncertainty estimation

30. Measurements using all available information with OmniFold

Benjamin Nachman

07/08/2020, 08:15

Simulation and all other topics

31. Lessons from Industry

Manuel Weber (Descartes Labs)

07/08/2020, 08:45

Simulation and all other topics

32. Reconstruction and machine learning for water Cherenkov detectors

Nick Prouse (TRIUMF), Patrick de Perio

07/08/2020, 09:30

Simulation and all other topics

33. Summary of Machine Learning Applications for the COHERENT Collaboration

Peibo An (Duke University)

07/08/2020, 09:50

Simulation and all other topics

34. Physics-informed Gaussian Process for Real-time Tuning and Control of Particle Accelerators

Adi Hanuka (SLAC)

07/08/2020, 10:10

Simulation and all other topics

43. Discussion topic 3

Reconstruction and whitepaper

46. Discussion topic 3

Interpretability and uncertainty estimation

47. XENON Summary Talks

Andrii Terliuk (MPIK, Heidelberg / Heidelberg University), Shixiao Liang (Rice University), Tianyu Zhu (Columbia University)

Reconstruction and whitepaper

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"