Learn how backpropagation powers neural networks, from the math and algorithm to real-world applications in AI, NLP, and autonomous systems
Recent ire from the media has focused on the high-power consumption of artificial neural nets (ANNs), yet popular discussion frequently conflates training and testing. Here, I aim to clarify the ways in which conversations involving the relative efficiency of ANNs and the human brain often miss the mark
Differences between deep learning and neural networks, including the architecture, complexity, performance, and use cases of the two concepts
Differences between deep learning and neural networks, including the architecture, complexity, performance, and use cases of the two concepts
An Interactive Node-Link Visualization of Convolutional Neural Networks Adam W. Harley Featured in Popular Science Abstract Convolutional neural networks are at the core of state-of-the-art approaches to a variety of computer vision tasks. Visualizations of neural networks typically take the form of static node-link diagrams, which illustrate only the structure of a network, rather than the behavior. Motivated by this observation, this paper presents a new interactive visualization of neural networks traine
This paper reevaluates the bias-variance trade-off in neural networks, revealing a bell-shaped variance curve and its impact on the double descent phenomenon
↓Skip to main content Denny’s Blog Recurrent Neural Networks Tutorial, Part 2 – Implementing a RNN with Python, Numpy and Theano 30 September 2015 This the second part of the Recurrent Neural Network Tutorial. The first part is here . Code to follow along is on Github. In this part we will implement a full Recurrent Neural Network from scratch using Python and optimize our implementation using Theano , a library to perform operations on a GPU. I will skip over some boilerplate code that is not
Abstract page for arXiv paper 1711.07971: Non-local Neural Networks
This explores the recent hypothesis that a neural network can produce perfect outputs while its internal wiring is a tangled mess — and what that broken organization costs it
# Artificial Neural Networks and Machine Learning – ICANN 2018 Artificial Neural Networks and Machine Learning – ICANN 2018 Springer International Publishing Chapter 1 Policy Learning Using SPSA Chapter 2 Simple Recurrent Neural Networks for Support Vector Machine Training Chapter 3 RNN-SURV: A Deep Recurrent Model for Survival Analysis Chapter 4 Do Capsule Networks Solve the Problem of Rotation Invariance for Traffic Sign Classification? Chapter 5 Balanced and Deterministic Weight-Sharing Helps Netw