Nature

Explainability Methods for Deep Learning Neural Networks

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...
Tech Xplore on MSN

Taming chaos in neural networks: A biologically plausible way

A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been ...
San Francisco Fed

Deep Neural Network Estimation in Panel Data Models

In this paper we study neural networks and their approximating power in panel data models. We provide asymptotic guarantees on deep feed-forward neural network estimation of the conditional mean, ...
dbta

TigerGraph Unveils its ML Workbench to Deliver Deep Learning and Graph Neural Network Frameworks

TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...
VentureBeat

10 years later, deep learning ‘revolution’ rages on, say AI pioneers Hinton, LeCun and Li

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Artificial intelligence (AI) pioneer ...
VentureBeat

DeepMind aims to marry deep learning and classic algorithms

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Will deep learning really live up to its ...