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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2407.12895 |
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| _version_ | 1866910532057956352 |
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| author | Augustine, Midhun T |
| author_facet | Augustine, Midhun T |
| contents | This paper discusses various theorems on the approximation capabilities of neural networks (NNs), which are known as universal approximation theorems (UATs). The paper gives a systematic overview of UATs starting from the preliminary results on function approximation, such as Taylor's theorem, Fourier's theorem, Weierstrass approximation theorem, Kolmogorov - Arnold representation theorem, etc. Theoretical and numerical aspects of UATs are covered from both arbitrary width and depth. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12895 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Universal Approximation Theorems Augustine, Midhun T Machine Learning Systems and Control This paper discusses various theorems on the approximation capabilities of neural networks (NNs), which are known as universal approximation theorems (UATs). The paper gives a systematic overview of UATs starting from the preliminary results on function approximation, such as Taylor's theorem, Fourier's theorem, Weierstrass approximation theorem, Kolmogorov - Arnold representation theorem, etc. Theoretical and numerical aspects of UATs are covered from both arbitrary width and depth. |
| title | A Survey on Universal Approximation Theorems |
| topic | Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2407.12895 |