Published June 4, 2025
| Version v2
Dataset
Open
Semi-Recurrent Neural Networks In IllustrisTNG And N-Body Simulations
Authors/Creators
- 1. University of St Andrews
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2.
Swinburne University of Technology
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3.
Kansas State University
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4.
Space Telescope Science Institute
Description
This is the official data repository for the MNRAS publication Modelling the galaxy-halo connection using semi-recurrent neural networks, and subsequent works Optimised neural network predictions of galaxy formation histories using semi-stochastic corrections and Evaluating the galaxy formation histories predicted by a neural network in pure dark matter simulations. For details on access and utilisation of the data and code, see documentation.pdf in the affiliated GitHub repository.
Files
Files
(16.2 GB)
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1.0 GB | Download |
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2.5 GB | Download |
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1.0 GB | Download |
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1.0 GB | Download |
Additional details
Funding
- UK Research and Innovation
- STFC St Andrews Physics 2019 DTP ST/T506448/1