Now showing items 1-3 of 3
Deep Networks for Pixel Level Inference with Applications to Medical Imaging
(Georgia Institute of Technology, 2017-09-26)
Sum-Product Networks: The Next Generation of Deep Models
The two main types of deep learning are function approximation and probability estimation. Function approximators like convolutional neural networks are robust and allow for real-time inference, but are very inflexible, ...
An overview of deep learning frameworks and an introduction to PyTorch
In this talk, you will get an exposure to the various types of deep learning frameworks – declarative and imperative frameworks such as TensorFlow and PyTorch. After a broad overview of frameworks, you will be introduced ...