'“The neural networks we tested—three publicly available neural nets and one that we developed ourselves—were able to determine the properties of each lens, including how its mass was distributed and how much it magnified the image of the background galaxy,” says the study’s lead author Yashar Hezaveh, a NASA Hubble postdoctoral fellow at KIPAC.
This goes far beyond recent applications of neural networks in astrophysics, which were limited to solving classification problems, such as determining whether an image shows a gravitational lens or not.'
Pretty fascinating stuff. Once you think about it, applying NNs to space makes a lot of sense. There is a ton of data to sift through and find patterns in. Amazing to think neural nets could crunch through this data in seconds, and point out areas of interest immediately. I wonder if NNs have been used in the search for exo planets yet.
This goes far beyond recent applications of neural networks in astrophysics, which were limited to solving classification problems, such as determining whether an image shows a gravitational lens or not.'
Pretty fascinating stuff. Once you think about it, applying NNs to space makes a lot of sense. There is a ton of data to sift through and find patterns in. Amazing to think neural nets could crunch through this data in seconds, and point out areas of interest immediately. I wonder if NNs have been used in the search for exo planets yet.