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The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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[06] Yoon Kim - Deep Latent Variable Models of Natural Language

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Manage episode 302418439 series 2982803
The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Yoon Kim is currently a Research Scientist at the MIT-IBM AI Watson Lab, and will be joining MIT as an assistant professor in 2021. Yoon’s research focuses on machine learning and natural language processing. His PhD thesis is titled "Deep Latent Variable Models of Natural Language", which he completed in 2020 at Harvard University. We discuss his work on uncovering latent structure in natural language, including continuous vector representations, tree structures, and grammars. We cover learning and variational inference methods that he developed during his PhD, and he offers a look at where latent variable models will be heading in the future. Episode notes: https://cs.nyu.edu/~welleck/episode6.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
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47 에피소드

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icon공유
 
Manage episode 302418439 series 2982803
The Thesis Review and Sean Welleck에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 The Thesis Review and Sean Welleck 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Yoon Kim is currently a Research Scientist at the MIT-IBM AI Watson Lab, and will be joining MIT as an assistant professor in 2021. Yoon’s research focuses on machine learning and natural language processing. His PhD thesis is titled "Deep Latent Variable Models of Natural Language", which he completed in 2020 at Harvard University. We discuss his work on uncovering latent structure in natural language, including continuous vector representations, tree structures, and grammars. We cover learning and variational inference methods that he developed during his PhD, and he offers a look at where latent variable models will be heading in the future. Episode notes: https://cs.nyu.edu/~welleck/episode6.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 에피소드

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