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[30] Dustin Tran - Probabilistic Programming for Deep Learning
Manage episode 302418415 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Dustin Tran is a research scientist at Google Brain. His research focuses on advancing science and intelligence, including areas involving probability, programs, and neural networks. Dustin’s PhD thesis is titled "Probabilistic Programming for Deep Learning", which he completed in 2020 at Columbia University. We discuss the intersection of probabilistic modeling and deep learning, including the Edward library and the novel inference algorithms and models that he developed in the thesis. - Episode notes: https://cs.nyu.edu/~welleck/episode30.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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47 episodes
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Manage episode 302418415 series 2982803
Content provided by The Thesis Review and Sean Welleck. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Thesis Review and Sean Welleck or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Dustin Tran is a research scientist at Google Brain. His research focuses on advancing science and intelligence, including areas involving probability, programs, and neural networks. Dustin’s PhD thesis is titled "Probabilistic Programming for Deep Learning", which he completed in 2020 at Columbia University. We discuss the intersection of probabilistic modeling and deep learning, including the Edward library and the novel inference algorithms and models that he developed in the thesis. - Episode notes: https://cs.nyu.edu/~welleck/episode30.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Find out more info about the show at https://cs.nyu.edu/~welleck/podcast.html - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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Similar to The Thesis Review
Get in-depth coverage of current and future trends in technology, and how they are shaping business, entertainment, communications, science, politics, and society.
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continue reading
Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
…
continue reading
Artificial Intelligence has suddenly gone from the fringes of science to being everywhere. So how did we get here? And where's this all heading? In this new series of Science Friction, we're finding out.
…
continue reading
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…
continue reading
Come dive into one of the curiously delightful conversations overheard at National Geographic’s headquarters, as we follow explorers, photographers, and scientists to the edges of our big, weird, beautiful world. Hosted by Peter Gwin and Amy Briggs.
…
continue reading
PT Inquest is an online journal club. Hosted by Jason Tuori, Megan Graham, and Chris Juneau, the show looks at an article every week and discusses how it applies to current physical therapy practice.
…
continue reading
We humans could have a bright future ahead of us that lasts billions of years. But we have to survive the next 200 years first. Join Josh Clark of Stuff You Should Know for a 10-episode deep dive that explores the future of humanity and finds dangers we have never encountered before lurking just ahead. And if we humans are alone in the universe, if we don't survive intelligent life dies out with us too.
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…
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