Predictive and generative neural networks
Machine learning applications based on neural networks have been flourishing over the years. In this report, we explore how to generate and predict random variables using neural networks, starting from well known methods, namely the inverse transform method and maximum likelihood techniques, then e...
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sg-ntu-dr.10356-1485142023-02-28T23:14:18Z Predictive and generative neural networks Chan, Keefe Frederique Elise Oggier School of Physical and Mathematical Sciences Frederique@ntu.edu.sg Science::Mathematics Machine learning applications based on neural networks have been flourishing over the years. In this report, we explore how to generate and predict random variables using neural networks, starting from well known methods, namely the inverse transform method and maximum likelihood techniques, then evolving towards scenarios where the need of predictive and generative neural networks arises Bachelor of Science in Mathematical Sciences 2021-04-29T01:59:29Z 2021-04-29T01:59:29Z 2021 Final Year Project (FYP) Chan, K. (2021). Predictive and generative neural networks. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/148514 https://hdl.handle.net/10356/148514 en application/pdf Nanyang Technological University |
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Science::Mathematics Chan, Keefe Predictive and generative neural networks |
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Machine learning applications based on neural networks have been flourishing over the years. In this report, we explore how to generate and predict random variables using neural networks,
starting from well known methods, namely the inverse transform method and maximum likelihood techniques, then evolving towards scenarios where the need of predictive and generative neural networks arises |
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Frederique Elise Oggier |
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Frederique Elise Oggier Chan, Keefe |
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Final Year Project |
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Chan, Keefe |
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Chan, Keefe |
title |
Predictive and generative neural networks |
title_short |
Predictive and generative neural networks |
title_full |
Predictive and generative neural networks |
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Predictive and generative neural networks |
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Predictive and generative neural networks |
title_sort |
predictive and generative neural networks |
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Nanyang Technological University |
publishDate |
2021 |
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https://hdl.handle.net/10356/148514 |
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