Super excited to FINALLY publish my first authored paper on the search for advanced extraterrestrial life using deep learning! Check out our Nature Astronomy paper here!
https://t.co/3FobupnF0L
Then we proceeded to write jankiest neural net in pure C (it literally seg faults if someone sneezed) so that it can run on LIGOโs realtime system it was so cursed lmao
Excited to publish our paper from my 2022 summer project on developing Deep Learning models to control nanometer precision optical instruments at @LIGO for detecting gravitational waves!
(๐ท Caltech LIGO)
https://t.co/swaIe2YgtX
We basically used a probabilistic GRU and a Kalman filter to reconstruct the dynamics of our mirrors, allowing us to use linear controls to solve the problem in simulation.
Super excited to FINALLY publish my first authored paper on the search for advanced extraterrestrial life using deep learning! Check out our Nature Astronomy paper here!
https://t.co/3FobupnF0L
Machine learning helps the Breakthrough Listen SETI project: it reduced the number of candidates identified in a 480-hour-long dataset by a factor of 100. From this, 8 signals worthy of further analysis have been found. Ma et al.: https://t.co/CSSS2JNmsu
Are we alone in the universe?
A team led by researchers at @UofT has figured out a new AI technique that could accelerate the search for extraterrestrial life - bringing us closer to answering this question! Published today in @NatureAstronomy.
More: https://t.co/aagzLRVJWD
Artificial intelligence seeks extraterrestrial intelligence. Breakthrough Listen develops a new machine learning system to search for potential signals from other civilizations.
https://t.co/gVKgTar6cX
Development of our new machine learning algorithm was led by @UofT undergraduate @peterma02 who started working with Berkeley SETI when he was in high school! https://t.co/Jn5oLVOQpx