Google Research has developed a new method to simulate neuroplasticity in AI. This greatly helps the memory abilities of AI ...

Learn how forward propagation works in neural networks using Python! This tutorial explains the process of passing inputs through layers, calculating activations, and preparing data for ...

Recently, the iGaN Laboratory led by Professor Haiding Sun at the School of Microelectronics, University of Science and Technology of China (USTC), together with the team of academician Sheng Liu from ...

Introduction: Accurate prediction of soil moisture content (SMC) is crucial for agricultural systems as it affects hydrological cycles, crop growth, and resource management. Considering the challenges ...

Abstract: This paper investigates the controllability of a broad class of recurrent neural networks widely used in theoretical neuroscience, including models of large-scale human brain dynamics.

Taking a page from the private insurance industry’s playbook, the Trump administration will launch a program next year to find out how much money an artificial intelligence algorithm could save the ...

In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...

Rep. John Moolenaar (R-Mich.), chair of the House Select Committee on the Chinese Communist Party, raised concerns Wednesday about the ongoing reliance of a potential TikTok spinoff on an algorithm ...

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...