2019-04-18
15:25 |
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2019-04-18
15:25 |
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Novelty Detection Meets Collider Physics
/ Li, Ying-Ying (speaker) (HKUST)
Novelty detection is the machine learning task to recognize data, which belong to an unknown pattern. Complementary to supervised learning, it allows to analyze data model-independently. [...]
2019 - 0:22:45.
LPCC Workshops; 3rd IML Machine Learning Workshop
External links: Talk details; Event details
In : 3rd IML Machine Learning Workshop
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2019-04-18
14:52 |
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The Tracking Machine Learning challenge
/ Rousseau, David (speaker) (LAL-Orsay, FR)
The HL-LHC will see ATLAS and CMS see proton bunch collisions reaching track multiplicity up to 10.000 charged tracks per event. Algorithms need to be developed to harness the increased combinatorial complexity. [...]
2019 - 0:32:50.
LPCC Workshops; 3rd IML Machine Learning Workshop
External links: Talk details; Event details
In : 3rd IML Machine Learning Workshop
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2019-04-18
14:31 |
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2019-04-18
14:25 |
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Uncertain Networks
/ Thompson, Jennifer (speaker) (ITP Heidelberg)
Machine learning methods are being increasingly and successfully applied to many different physics problems. However, currently uncertainties in machine learning methods are not modelled well, if at all. [...]
2019 - 0:33:25.
LPCC Workshops; 3rd IML Machine Learning Workshop
External links: Talk details; Event details
In : 3rd IML Machine Learning Workshop
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2019-04-18
11:11 |
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2019-04-18
10:52 |
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2019-04-18
10:39 |
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2019-04-18
10:30 |
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Gauge Fields in Deep Learning
/ Welling, Max (speaker) (University of Amsterdam)
Joint work with Taco Cohen, Maurice Weiler and Berkay Kicanaoglu
Gauge field theory is the foundation of modern physics, including general relativity and the standard model of physics. It describes how a theory of physics should transform under symmetry transformations [...]
2019 - 1:07:02.
CERN Colloquium
External link: Event details
In : Gauge Fields in Deep Learning
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2019-04-18
10:23 |
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Applying Generative Models to Scientific Research
/ Ratnikov, Fedor (speaker) (Yandex School of Data Analysis (RU))
Surrogate generative models demonstrate extraordinary progress in current years. Although most applications are dedicated to image generation and similar commercial
goals, this approach is also very promising for natural sciences, especially for tasks like fast event simulation in HEP experiments. [...]
2019 - 0:30:54.
LPCC Workshops; 3rd IML Machine Learning Workshop
External links: Talk details; Event details
In : 3rd IML Machine Learning Workshop
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