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Accelerating Physics with ML@MIT

28 January 2023 to 2 February 2023
US/Eastern timezone

Contribution List

42 / 42
18. Workshop goals
Philip Coleman Harris (Massachusetts Inst. of Technology (US))
30/01/2023, 09:00
19. Inference-as-a-service in high energy physics
William Patrick Mccormack (Massachusetts Inst. of Technology (US))
30/01/2023, 09:30
20. Inference-as-a-service in gravitational-wave physics
Alec Gunny, Alec Gunny
30/01/2023, 10:00
21. Searches for compact binary coalescences-I
Damon Beveridge, Damon Beveridge
30/01/2023, 11:00
22. Searches for compact binary coalescences-II
Ethan Marx (MIT), Ethan Marx
30/01/2023, 11:15
23. Denoising methods-I
Saleem Muhammed
30/01/2023, 11:30
24. Denoising methods-II
Dr Chia-Jui Chou (National Yang Ming Chiao Tung University), Chia-Jui Chou
30/01/2023, 11:45
25. Parameter estimation methods
Maximillian Dax
30/01/2023, 12:00
16. The Challenges of Identification, Classification and Inference for Time-domain Astrophysics with Big Data
Ashley Villar
30/01/2023, 14:00
17. Multi-messenger astronomy infrastructure for optical follow-ups
Konstantin Malanchev
30/01/2023, 14:30
29. Challenges for identifying and following-up the next kilonova
Niharika Sravan
30/01/2023, 15:00
9. Software Infrastructure Challenges for IaaS with HEP (20'+10')
Kevin Pedro (Fermi National Accelerator Lab. (US))
30/01/2023, 16:00
10. SONIC Inference as a Service for Point Clouds
Yongbin Feng (Fermi National Accelerator Lab. (US))
30/01/2023, 16:35
11. ML GPU deployments for Neutrino Reconstruction
Tingjun Yang (Fermi National Accelerator Lab. (US))
30/01/2023, 17:00
12. Anomaly detection for EM
Daniel Muthukrishna (MIT)
31/01/2023, 09:00
13. Anomaly detection in GW
Ryan Raikman (Carnegie Mellon University)
31/01/2023, 09:20
14. MLY Pipeline
Vasileios Skliris (Cardiff University)
31/01/2023, 09:40
15. Anomaly Detection in HEP
Katya Govorkova (Massachusetts Inst. of Technology (US))
31/01/2023, 10:00
26. Point-Voxel CNN
Zhijian Liu
31/01/2023, 11:00
27. Sparse GPU implementations
Haotian Tang
31/01/2023, 11:30
28. Computing at the Massachusetts Green High Performance Center
Chris Hill
31/01/2023, 12:00
36. ML Workflows on NSERC
Steven Farrell (Lawrence Berkeley National Laboratory)
31/01/2023, 14:00
39. ML Algorithms at SDSC/NRP
Frank Wurthwein (UCSD)
31/01/2023, 14:30
37. HPC Discussion
31/01/2023, 14:50
30. Machine learning applications in Icecube
Josh Peterson
01/02/2023, 09:00
31. Pointing to a Supernova
Kate Scholberg
01/02/2023, 09:20
32. Binary neutron star early warning detection using ML
Alistair Mcleod
01/02/2023, 09:40
33. Localization and waveform extraction for compact binary coalescences
Chayan Chatterjee
01/02/2023, 09:55
34. Unsupervised Learning for TESS Variable Stars
Jeroen Audenaert
01/02/2023, 10:10
38. Contextualized machine learning for applied data science
Ben Lengerich
01/02/2023, 10:30
40. HEP
William Patrick Mccormack (Massachusetts Inst. of Technology (US))
01/02/2023, 11:30
41. GW
Deep Chatterjee, Deep Chatterjee, Deep Chatterjee
01/02/2023, 11:50
42. EM Astronomy
Daniel Muthukrishna, Daniel Muthukrishna, Daniel Muthukrishna (MIT)
01/02/2023, 12:10
1. LIGO O4 Hackathon
2. LIGO O4 Hackathon
6. LIGO Run O4 Hackathon
7. LIGO Run O4 Hackathon
8. test
Philip Coleman Harris (Massachusetts Inst. of Technology (US))
35. Unsupervised Learning for TESS Variable Stars
Jeroen Audenaert
4. Workshop
3. Workshop-- Hackthon session #1
Alec Gunny (MIT)

Work on ML infrastructure and code deployment and debugging
5. Wrap up
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