# Machine Learning and the future of Supernova Cosmology

arXiv: https://arxiv.org/abs/1908.02315 · HTML: https://mlsanity.com/paper/1908.02315/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Aug 2019.

## Built on by (most cited first, 2 of 2)

- [Neural Networks Optimized by Genetic Algorithms in Cosmology](https://mlsanity.com/paper/2209.02685/) (2022)
- [Explainable classification of astronomical uncertain time series](https://mlsanity.com/paper/2210.00869/) (2022)

## Abstract (arXiv)

Machine Learning methods will play a fundamental role in our ability to optimize the science output from the next generation of large scale surveys. Given the peculiarities of astronomical data, it is crucial that algorithms are adapted to the data situation at hand. In this comment, I review the recent efforts towards the development of automatic systems to identify and classify supernova with the goal of enabling their use as cosmological standard candles.