Gated recurrent unit

The Math Behind Gated Recurrent Units

Towards Data Science

Gated Recurrent Units (GRUs) are a powerful type of recurrent neural network (RNN) designed to handle sequential data efficiently. In this article, we’ll explore what GRUs are, and…

Gated Recurrent Units (GRU)

Dive intro Deep Learning Book

As RNNs and particularly the LSTM architecture ( Section 10.1 ) rapidly gained popularity during the 2010s, a number of papers began to experiment with simplified architectures in hopes of retaining t...

Gated Recurrent Units (GRU) — Improving RNNs

Towards Data Science

In this article, I will explore a standard implementation of recurrent neural networks (RNNs): gated recurrent units (GRUs). GRUs were introduced in 2014 by Kyunghyun Cho et al. and are an improvement...

Unlocking Sequential Intelligence: The Power and Efficiency of Gated Recurrent Units in Deep…

Python in Plain English

Unlocking Sequential Intelligence: The Power and Efficiency of Gated Recurrent Units in Deep Learning Abstract Context: Gated Recurrent Units (GRU) has emerged as a formidable architecture within the...

Deep Dive into Gated Recurrent Units (GRU): Understanding the Math behind RNNs

Towards AI

Gated Recurrent Unit (GRU) is a simplified version of Long Short-Term Memory (LSTM). Let’s see how it works in this article. Photo by Laila Gebhard on Unsplash This article will explain the working o...

Long Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 Way

Towards Data Science

Hi All, welcome to my blog “Long Short Term Memory and Gated Recurrent Unit’s Explained — ELI5 Way” this is my last blog of the year 2019. My name is Niranjan Kumar and I’m a Senior Consultant Data…

Recurrent Neural Networks — Part 4

Towards Data Science

In this blog post, we introduce the concept of gated recurrent units. Having fewer parameters than the LSTM, yet still empirically yield similar performance.

Understanding Gated Recurrent Neural Networks

Analytics Vidhya

I strongly recommend to first know how a Recurrent Neural Network algorithm works to get along with this post of Gated RNN’s. Before getting into the details, let us first discuss about the need to…

GRU Recurrent Neural Networks — A Smart Way to Predict Sequences in Python

Towards Data Science

A visual explanation of Gated Recurrent Units including an end to end Python example of their use with real-life data Continue reading on Towards Data Science

A deep dive into the world of gated Recurrent Neural Networks: LSTM and GRU

Analytics Vidhya

RNNs can further be improved using the gated RNN architecture. LSTM and GRU are some examples of this. The articles explain both the architectures in detail.

GRU

PyTorch documentation

Applies a multi-layer gated recurrent unit (GRU) RNN to an input sequence. For each element in the input sequence, each layer computes the following function: where h t h_t h t is the hidden state a...

[NIPS 2017/Part 1] Gated Recurrent Convolution NN for OCR with Interactive Code [ Manual Back Prop…

Towards Data Science

So this is the first part of implementing Gated Recurrent Convolutional Neural Network. And I will cover one by one, so for today lets implement a simple Recurrent Convolutional Neural Network as a…