Decision-making often involves trial and error, but conventional models assume we always act optimally based on past ...

This week, I dug into some open ai latest news that feels almost like a spy thriller. You’ve got nation-states playing games ...

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A Memory Augmented Neural Network (MANN) is an extension to an RNN which enables it to save large amount of data to a memory object which is dimensionally separated from the Neural Network. This paper ...

Neural network-assisted (NNA) Kalman filters provide an effective solution to addressing the filtering issues involving partially unknown system information by incorporating neural networks to compute ...

Key Takeaways The transition requires upskilling in Python, statistics, and machine learning.Practical experience with ...

Rats exhibit significant recovery of locomotor function following incomplete spinal cord injuries, albeit with altered gait expression and reduced speed and stepping frequency. These changes likely ...

Farouk and Jinsong (2022) predicted the bond strength of UHPC-NSC interface by two kinds of methods, such as artificial neural network and multiple linear regression. The reliability of the artificial ...

Mechanistic modeling with low-rank recurrent networks uncovers the relationship between network connectivity, neural dynamics, and selection modulation mechanisms in context-dependent computation.