Generative Adversarial Networks, Autoencoders and TensorRT

Corey Adams, Argonne National Laboratory
Nikil Ravi, University of Illinois at Urbana-Champaign
Webinar Beginner
Generative Adversarial Networks, Autoencoders and TensorRT

This module will introduce applications of GANS and autoencoders in scientific research, and the use of NVIDIA TensorRT to optimize AI models for accelerated inference.

Day and Time: January 13, 3-5 p.m. US CT

This session is a part of the ALCF AI for Science Training Series

About the Speakers

Corey Adams is an assistant computer scientist at the Argonne Leadership Computing Facility.  Originally a high-energy physicist working on neutrino physics problems,  he now works on applying deep learning and machine learning techniques to science problems – and still neutrino physics – on high-performance supercomputers.  He has experience in classification, segmentation, sparse convolutional neural networks as well as running machine learning training at scale.