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Video: Addressing Key Science Challenges with Adversarial Neural Networks

In this video from the 2018 HPC User Forum in Tucson, Wahid Bhimji from NERSC presents: Addressing Key Science Challenges with Adversarial Neural Networks.

Machine Learning and Deep Learning are increasingly used to analyze scientific data, in fields as diverse as neuroscience, climate science and particle physics. In this page you will find links to examples of scientific use cases using deep learning at NERSC, information about what deep learning packages are available at NERSC, and details of how to scale up your deep learning code on Cori to take advantage of the compute power available from Cori’s KNL nodes.”

Wahid Bhimji is a Big Data Architect in the Data and Analytics Services team at NERSC. His current interests include machine learning, databases and data management. Wahid has worked for many years in Scientific Computing and Data Analysis in Academia and Government and has a Ph.D. in High-Energy Particle Physics.

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