@article {670971,
	title = {The Role of Machine Learning in the Next Decade of Cosmology},
	journal = {Bulletin of the American Astronomical Society},
	volume = {51},
	number = {14},
	year = {2019},
	abstract = {In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.},
	url = {https://arxiv.org/abs/1902.10159},
	author = {Ntampaka, Michelle and Camille Avestruz and Steven Boada and Joao Caldeira and Jessi Cisewski-Kehe and Di Stefano, Rosanne and Dvorkin, Cora and August E. Evrard and Arya Farahi and Finkbeiner, Doug and Genel, Shy and Goodman, Alyssa and alia}
}
