Jian Huang - Colloquium Speaker

Professor, Department of Statistics and Actuarial Science, University of Iowa
Date: 
Thursday, September 9, 2021 - 3:30pm
Colloquium Title: 
Generative Monte Carlo
Location: 
Meet and Greet at 3:00 pm in 241 SH / Talk at 3:30 pm in 61 SH

Abstract:

Learning a probability distribution based on a random sample and sampling from a given distribution are two basic problems in statistics and machine learning. These problems have been studied intensively as two separate questions in the literature. In recent years, generative learning methods such as generative adversarial networks have been proven effective in learning distributions. In this talk, we consider the problems of sampling from a conditional distribution and sampling from an unnormalized distribution to illustrate that learning and sampling are two sides of the same coin in the context of generative learning. The key to the success of such an approach is the power of deep neural networks in approximating multidimensional functions. Numerical experiments on image generation using benchmark datasets and simulation from multimodal distributions demonstrate that generative Monte Carlo has the potential to be a useful addition to the toolbox for sampling.

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Topic: Colloquia: Department of Statistics and Actuarial Science, The University of Iowa

Time: September 9, 2021 03:30 PM Central Time (US and Canada)

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Meeting ID: 989 2869 3758

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Meeting ID: 989 2869 3758