Disclosing the undisclosable: Section 112(a) challenges for artificial intelligence patents

Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldstein & Fox PLLC discuss challenges in meeting patent law's disclosure requirements for inventions involving artificial intelligence, ...
eLife

“What” × “When” working memory representations using Laplace Neural Manifolds

The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...
IEEE

Generating Spiking Neural Network Code Libraries for Embedded Systems

Abstract: Spiking neural networks (SNNs) are attractive algorithms that pose numerous potential advantages over traditional neural networks. One primary benefit of SNNs is that they may be run ...
INSPIRE

Neural Minimum Weight Perfect Matching for Quantum Error Codes

Realizing the full potential of quantum computation requires Quantum Error Correction (QEC). QEC reduces error rates by encoding logical information across redundant ...
Hosted on MSN

Activation functions in neural networks: Types and examples

In this video, we will see What is Activation Function in Neural network, types of Activation function in Neural Network, why to use an Activation Function and which Activation function to use. The ...
TechCrunch

Cyber giant F5 Networks says government hackers had ‘long-term’ access to its systems, stole code and customer data

Cybersecurity firm F5 Networks says government-backed hackers had “long-term, persistent access” to its network, which allowed them to steal the company’s source code and customer information. In a ...
CSOonline

Source code and vulnerability info stolen from F5 Networks

IT and security leaders should install latest patches from the application delivery and security vendor after suspected nation-state hack. CSOs with equipment from F5 Networks in their environment ...
Scientific Research Publishing

Prediction of Building Displacements during Wind Gusts Using Support Vector Regression and Deep Neural Network ()

The significance of artificial intelligence in contemporary human activities cannot be underestimated. Although the application of this technology in structural engineering is not recent, advancements ...
GitHub

Legend-KINN: A Legendre Polynomial-Based Kolmogorov-Arnold-Informed Neural Network for Efficient PDE Solving

This is the PyTorch implementation of Legend-KINN, proposed by our paper "Legend-KINN: A Legendre Polynomial-Based Kolmogorov-Arnold-Informed Neural Network for Efficient PDE Solving", published in ...