Open AccessDissertation
Latent Variable Machine Learning Algorithms: Applications in a Nuclear Physics Experiment
Robert Solli
- 01 Jan 2019
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About: The article was published on 01 Jan 2019. and is currently open access. The article focuses on the topics: Latent variable.
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Citations
Unsupervised learning for identifying events in active target experiments
R. Solli,D. Bazin,Morten Hjorth-Jensen,Morten Hjorth-Jensen,Michelle Kuchera,Ryan R. Strauss,Ryan R. Strauss +6 more
TL;DR: Novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC), and finds that a K-means algorithm applied to the simulated data in the VGG16 latent space forms almost perfect clusters.
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Going deeper with convolutions
Christian Szegedy,Wei Liu,Yangqing Jia,Pierre Sermanet,Scott Reed,Dragomir Anguelov,Dumitru Erhan,Vincent Vanhoucke,Andrew Rabinovich +8 more
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TL;DR: Inception as mentioned in this paper is a deep convolutional neural network architecture that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14).