This valuable computational study presents a conceptually simple and biologically plausible reinforcement-learning framework for motor learning based on policy-gradient methods. The evidence ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study investigates fault diagnosis, encompassing fault detection, isolation, and ...
Which learning goals must individual computational elements pursue to contribute to a network-level task solution? This local understanding is missing in both biological, but also artificial neural ...
Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China School of Information and Control ...
PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax ...
In 1957, Rosenblatt published pioneering work on the first machine learning algorithm for artificial neurons, known as the perceptron. He helped revolutionize the field of artificial intelligence ...
Assessing power-law cross-correlations between a pair – or among a set – of processes is of great significance in diverse fields of analyses ranging from neuroscience to financial markets. In most ...
HealthTree Cure Hub: A Patient-Derived, Patient-Driven Clinical Cancer Information Platform Used to Overcome Hurdles and Accelerate Research in Multiple Myeloma Adversarial images represent a ...
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