Residual 1D CNN for Low SFR Surface Density Regression: A Design Note
Fuente:
arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866908391501201408 |
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| author | Yu, Po-Chieh |
| author_facet | Yu, Po-Chieh |
| contents | This technical note describes the design and modular implementation of a one-dimensional convolutional neural network (1D CNN) adapted from residual networks (ResNet), developed for photometric regression tasks with an emphasis on low star formation rate surface density ($Σ_{\mathrm{SFR}}$) inference. The model features residual block structures optimized for sparse targets, with optional loss weighting and diagnostic tools for analyzing residual behavior. The implementation (version \texttt{v1.4}) originated during a collaborative project and is documented here independently. No external data are reproduced or analyzed. This note provides a reusable architectural reference for scalar regression problems in astronomy and related domains. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_02705 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Residual 1D CNN for Low SFR Surface Density Regression: A Design Note Yu, Po-Chieh Instrumentation and Methods for Astrophysics This technical note describes the design and modular implementation of a one-dimensional convolutional neural network (1D CNN) adapted from residual networks (ResNet), developed for photometric regression tasks with an emphasis on low star formation rate surface density ($Σ_{\mathrm{SFR}}$) inference. The model features residual block structures optimized for sparse targets, with optional loss weighting and diagnostic tools for analyzing residual behavior. The implementation (version \texttt{v1.4}) originated during a collaborative project and is documented here independently. No external data are reproduced or analyzed. This note provides a reusable architectural reference for scalar regression problems in astronomy and related domains. |
| title | Residual 1D CNN for Low SFR Surface Density Regression: A Design Note |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2506.02705 |