Deep Learning and Automatic Differentiation from Theano to PyTorch - insideHPC

In this video from CSCS-ICS-DADSi Summer School, Atilim Güneş Baydin presents: Deep Learning and Automatic Differentiation from Theano to PyTorch. 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. In recent centuries, developments in science and technology brought us closer to explore the expanding universe, discover unknown particles like bosons or find out how and why a society interacts and reacts. To explain the fascinating phenomena of nature, Natural scientists develop complex'mechanistic models' of deterministic or stochastic nature. But the hard question is how to choose the best model for our data or how to calibrate the model given the data. 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.