[CMU AI Seminar] Oct 19 at 12pm (Zoom) -- Stefano Ermon (Stanford) -- Generative Modeling by Estimating Gradients of the Data Distribution -- AI Seminar sponsored by Morgan Stanley

[Shaojie Bai]

Hi all,

Just a reminder that the CMU AI Seminar is tomorrow 12pm-1pm:
https://cmu.zoom.us/j/99631487756?pwd=a2NORWwwaWlybjNZemo3N2h1RkZ2dz09  .

Stefano Ermon (Stanford) will be talking about his group's latest research
on generative modeling with score-based methods.

Thanks,
Shaojie

On Thu, Oct 14, 2021 at 5:41 PM Shaojie Bai <shaojieb at cs.cmu.edu> wrote:

> Dear all,
>
> We look forward to seeing you *next Tuesday (10/19)* from *1**2:00-1:00
> PM (U.S. Eastern time)* for the next talk of our *CMU AI seminar*,
> sponsored by Morgan Stanley
> <https://www.morganstanley.com/about-us/technology/>.
>
> To learn more about the seminar series or see the future schedule, please
> visit the seminar website <http://www.cs.cmu.edu/~aiseminar/>.
>
> On 10/19, *Stefano Ermon* (Stanford) will be giving a talk on "*Generative
> Modeling by Estimating Gradients of the Data Distribution*" and their
> research on score-based models.
>
> *Title*: Generative Modeling by Estimating Gradients of the Data
> Distribution
>
> *Talk Abstract*: Existing generative models are typically based on
> explicit representations of probability distributions (e.g., autoregressive
> or VAEs) or implicit sampling procedures (e.g., GANs). We propose an
> alternative approach based on modeling directly the vector field of
> gradients of the data distribution (scores). Our framework allows flexible
> architectures, requires no sampling during training or the use of
> adversarial training methods. Additionally, score-based generative models
> enable exact likelihood evaluation through connections with normalizing
> flows. We produce samples comparable to GANs, achieving new
> state-of-the-art inception scores, and competitive likelihoods on image
> datasets.
>
> *Speaker Bio*:  Stefano Ermon is an Assistant Professor of Computer
> Science in the CS Department at Stanford University, where he is affiliated
> with the Artificial Intelligence Laboratory, and a fellow of the Woods
> Institute for the Environment. His research is centered on techniques for
> probabilistic modeling of data and is motivated by applications in the
> emerging field of computational sustainability. He has won several awards,
> including Best Paper Awards (ICLR, AAAI, UAI and CP), a NSF Career Award,
> ONR and AFOSR Young Investigator Awards, a Sony Faculty Innovation Award, a
> Hellman Faculty Fellowship, Microsoft Research Fellowship, Sloan
> Fellowship, and the IJCAI Computers and Thought Award. Stefano earned his
> Ph.D. in Computer Science at Cornell University in 2015.
>
> *Zoom Link*:
> https://cmu.zoom.us/j/99631487756?pwd=a2NORWwwaWlybjNZemo3N2h1RkZ2dz09
>
> Thanks,
> Shaojie Bai (MLD)
>
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