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[13] Adji Bousso Dieng - Deep Probabilistic Graphical Modeling
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Manage episode 302418432 series 2982803
Indhold leveret af The Thesis Review and Sean Welleck. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Thesis Review and Sean Welleck eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Adji Bousso Dieng is currently a Research Scientist at Google AI, and will be starting as an assistant professor at Princeton University in 2021. Her research focuses on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data. Her PhD thesis is titled "Deep Probabilistic Graphical Modeling", which she completed in 2020 at Columbia University. We discuss her work on combining graphical models and deep learning, including models and algorithms, the value of interpretability and probabilistic models, as well as applications and making an impact through research. Episode notes: https://cs.nyu.edu/~welleck/episode13.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.buymeacoffee.com/thesisreview
…
continue reading
47 episoder
MP3•Episode hjem
Manage episode 302418432 series 2982803
Indhold leveret af The Thesis Review and Sean Welleck. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af The Thesis Review and Sean Welleck eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
Adji Bousso Dieng is currently a Research Scientist at Google AI, and will be starting as an assistant professor at Princeton University in 2021. Her research focuses on combining probabilistic graphical modeling and deep learning to design models for structured high-dimensional data. Her PhD thesis is titled "Deep Probabilistic Graphical Modeling", which she completed in 2020 at Columbia University. We discuss her work on combining graphical models and deep learning, including models and algorithms, the value of interpretability and probabilistic models, as well as applications and making an impact through research. Episode notes: https://cs.nyu.edu/~welleck/episode13.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.buymeacoffee.com/thesisreview
…
continue reading
47 episoder
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