Deep Learning in the Natural Sciences: Applications to Physics
Machine learning is increasingly being used not only in engineering applications such as computer vision and speech recognition, but in data analysis for the natural sciences. Here we describe applications of deep learning to four areas of experimental sub-atomic physics — high-energy physics, antim...
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| Published in | Braverman Readings in Machine Learning. Key Ideas from Inception to Current State pp. 269 - 297 |
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| Main Authors | , |
| Format | Book Chapter |
| Language | English |
| Published |
Cham
Springer International Publishing
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| Series | Lecture Notes in Computer Science |
| Online Access | Get full text |
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| Summary: | Machine learning is increasingly being used not only in engineering applications such as computer vision and speech recognition, but in data analysis for the natural sciences. Here we describe applications of deep learning to four areas of experimental sub-atomic physics — high-energy physics, antimatter physics, neutrino physics, and dark matter physics. |
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| ISBN: | 9783319994918 3319994913 |
| ISSN: | 0302-9743 1611-3349 |
| DOI: | 10.1007/978-3-319-99492-5_12 |