This repository contains an experimental PyTorch implementation exploring the NoProp algorithm, presented in the paper "NOPROP: TRAINING NEURAL NETWORKS WITHOUT BACK-PROPAGATION OR FORWARD-PROPAGATION ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Hi, thanks for your excellent work on this project. The research and the JAX implementation are both fantastic resources. I wanted to share that I have developed a PyTorch implementation of MeanFlow ...

Abstract: The characteristics of recurrent and functional reduction in RNNs (Recurrent Neural Networks) may cause an inefficient execution in conventional hardware such as CPU (Central Processing Unit ...

Abstract: Random neural network (RNN) is an analytically tractable spiked neural network model that has been implemented in software for a wide range of applications for over a decade. This paper ...