Article 3BP92 Deep Learning and Automatic Differentiation from Theano to PyTorch

Deep Learning and Automatic Differentiation from Theano to PyTorch

by
Rich Brueckner
from High-Performance Computing News Analysis | insideHPC on (#3BP92)
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Inquisitive minds want to know what causes the universe to expand, how M-theory binds the smallest of the small particles or how social dynamics can lead to revolutions. "The way that statisticians answer these questions is with Approximate Bayesian Computation (ABC), which we learn on the first day of the summer school and which we combine with High Performance Computing. The second day focuses on a popular machine learning approach 'Deep-learning' which mimics the deep neural network structure in our brain, in order to predict complex phenomena of nature."

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