IEEE

Recursive Neural Network POS Tagger

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.
来自MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

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 ...
GitHub

recursive-neural-networks

Add a description, image, and links to the recursive-neural-networks topic page so that developers can more easily learn about it.
Frontiers

Network structure influences self-organized criticality in neural networks with dynamical ...

The brain criticality hypothesis has been a central research topic in theoretical neuroscience for two decades. This hypothesis suggests that the brain operates near the critical point at the boundary ...
Scientific Research Publishing

Dhiman, A. and Hu, Y. (2023) Physics Informed Neural Network for Option Pricing.

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...
IEEE

A Comparison between Recursive Neural Networks and Graph Neural Networks

Abstract: Recursive neural networks (RNNs) and graph neural networks (GNNs) are two connectionist models that can directly process graphs. RNNs and GNNs exploit a similar processing framework, but ...