This is the code repository for Dynamic Neural Network Programming with PyTorch [Video], published by Packt. It contains all the supporting project files necessary to work through the video course ...

The process of creating a PyTorch neural network for regression consists of six steps ... but doesn't assume you know very much about PyTorch. The complete source code for the demo program, and the ...

Figure 2: Example MNIST Images Most neural network libraries, including PyTorch, scikit and Keras ... Therefore, to load the saved model from another program, you must place the code that defines the ...

This is a PyTorch implementation of the box convolution layer as introduced in the 2018 NeurIPS paper: Burkov, E., & Lempitsky, V. (2018) Deep Neural Networks with Box Convolutions. Advances in Neural ...

A consistent coding style makes your code easier to read ... and guidelines of the neural network framework and library you are using, such as TensorFlow, PyTorch, or Keras.

This document serves as user manual for HydraGNN, a scalable graph neural network (GNN) architecture that allows for a simultaneous prediction of multiple target properties using multi-task learning ...

Spiking neural network (SNN), a sub-category of brain-inspired neural networks, mimics the biological neural codes, dynamics, and circuitry. One particular observation is that the brain performs ...