A research team of mathematicians and computer scientists has used machine learning to reveal new mathematical structure within the theory of finite groups. By training neural networks to recognise ...
Abstract: Supervised learning problems with side information in the form of a network arise frequently in applications in genomics, proteomics and neuroscience. For example, in genetic applications, ...
Macy is a writer on the AI Team. She covers how AI is changing daily life and how to make the most of it. This includes writing about consumer AI products and their real-world impact, from ...
Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...
The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...
What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...
This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...
Abstract: In this research, we present a novel method for solving non-linear, time-dependent partial differential equations (PDEs) using active learning combined with Gaussian Process Regression (GPR) ...
A new approach to the local and global explanation based on selecting a convex hull constructed for the finite number of points around an explained instance is proposed. The convex hull allows us to ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback