2-7 June 2019
Simon Fraser University
America/Vancouver timezone
Welcome to the 2019 CAP Congress Program website! / Bienvenue au siteweb du programme du Congrès de l'ACP 2019 !

Deep Generative Models and Applications to Physics

4 Jun 2019, 11:15
HC 126 (Simon Fraser University)

HC 126

Simon Fraser University


Payam Mousavi (MDA / MAXAR)


Generative models leveraging the recent advances in Deep Neural Networks (DNNs) have enabled incredible applications in diverse fields such as, machine vision, speech, and finance. After giving a brief historical perspective, this presentation introduces the concepts and principles behind deep generative models, focusing mainly on an important sub-class, namely, Generative Adversarial Networks (GANs). Using selected examples, we briefly explore applications of generative models to problems in physics and their implications. The presentation concludes with recent results using GANs for image synthesis and manipulation of satellite imagery to facilitate the training of object detection/segmentation networks.

Primary author

Payam Mousavi (MDA / MAXAR)

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