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[28] Karen Ullrich - A Coding Perspective on Deep Latent Variable Models
Manage episode 302418417 series 2982803
Contenu fourni par The Thesis Review and Sean Welleck. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par The Thesis Review and Sean Welleck ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
Karen Ullrich is a Research Scientist at FAIR. Her research focuses on the intersection of information theory and probabilistic machine learning and deep learning. Karen's PhD thesis is titled "A coding perspective on deep latent variable models", which she completed in 2020 at The University of Amsterdam. We discuss information theory & the minimum description length principle, along with her work in the thesis on compression and communication. Episode notes: https://cs.nyu.edu/~welleck/episode28.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and 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 302418417 series 2982803
Contenu fourni par The Thesis Review and Sean Welleck. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par The Thesis Review and Sean Welleck ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.
Karen Ullrich is a Research Scientist at FAIR. Her research focuses on the intersection of information theory and probabilistic machine learning and deep learning. Karen's PhD thesis is titled "A coding perspective on deep latent variable models", which she completed in 2020 at The University of Amsterdam. We discuss information theory & the minimum description length principle, along with her work in the thesis on compression and communication. Episode notes: https://cs.nyu.edu/~welleck/episode28.html Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and 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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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 ...
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continue reading
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…
continue reading
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…
continue reading
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…
continue reading
I discuss a variety of topics in both the natural and social sciences, exploring the many fascinating insights that the scientific method yields about the world around us.
…
continue reading
How can we, humans, look at our relationship to nature differently? In season three of Going Wild, on top of stories about animals, we invite you to journey through the entire ecological web — from the tiniest of life forms to apex predators — alongside the scientists, activists and adventurers who study it. Wildlife biologist and host Dr. Rae Wynn-Grant has been studying wild animals in their natural habitats all over the world for years. Our award-winning podcast takes you inside the hidde ...
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