Application of Machine Learning and Deep Learning in High Energy Phenomenology

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dc.contributor.authorChawla, Harshita
dc.date.accessioned2026-10-06T09:39:48Z
dc.date.available2026-10-06T09:39:48Z
dc.date.issued2022-05-18
dc.description.abstractArtificial intelligence has vast applications in every field and it certainly has a lot of an application in the field of high-energy phenomenology. In this, we are going to explain how we can use machine learning and deep learning applications in computing important parameter regions and exploring the parameter space of new models. First, we will discuss deep learning models and machine learning algorithms in detail and then we will apply our knowledge to some basic models and then subsequently discuss their role in the high-energy phenomenology. We will also see how some of the applications that we can explore in physics and how can be applied.
dc.identifier.urihttp://nits.ndl.gov.in/handle/123456789/148
dc.language.isoen
dc.publisherDepartment of Physics
dc.relation.ispartofseriesD1552
dc.titleApplication of Machine Learning and Deep Learning in High Energy Phenomenology
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