Implementation of Neural Nets in PyTorch

Implementation of Neural Nets in PyTorch [Slides]

Nick Geneva

In this seminar we review and discuss the implementation of two different neural nets. First we discuss using mixture density networks to fit Gaussian distributions to a set of toy data and implementing a custom lost function in PyTorch. Second we review and discuss the implementation of a simple Bayesian neural network for a toy classification problem

Reference: C. Bishop, Pattern Recognition and Machine Learning, Chapter 05, Springer, 2006.