Adji Bousso Dieng's guest appearances

Adji Bousso Dieng

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

The Thesis Review

Chelsea Finn

Sebastian Ruder

Kenneth Stanley

Burr Settles

Sanmi Koyejo

Dario Amodei

Jianxiong Xiao

Kate Darling

Jason Holmberg

Lotte Bransen

Christopher Berner

David Spiegelhalter

Kristen Grauman

Stephen Merity

George Papamakarios

OwlTail

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.htmlFollow 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.htmlSupport The Thesis Review at www.buymeacoffee.com/thesisreview

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: <a href="https://cs.nyu.edu/~welleck/episode13.html" rel="nofollow" target="_blank">https://cs.nyu.edu/~welleck/episode13.html</a> Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter, and find out more info about the show at <a href="https://cs.nyu.edu/~welleck/podcast.html" rel="nofollow" target="_blank">https://cs.nyu.edu/~welleck/podcast.html</a> Support The Thesis Review at <a href="http://www.buymeacoffee.com/thesisreview" rel="nofollow" target="_blank">www.buymeacoffee.com/thesisreview</a>

[13] Adji Bousso Dieng - Deep Probabilistic Graphical Modeling

In this episode, I'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University to discuss two of her recent papers, “Noisin: Unbiased Regularization for Recurrent Neural Networks” and “TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency.” We dive into the details behind both of these papers and learn a ton along the way.

Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk #160