Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...

Overview Books provide a deeper understanding of AI concepts beyond running code or tutorials.Hands-on examples and practical ...

Abstract: Convolutional Neural Network (CNN) is a popular model in computer vision and has the advantage of making good use of the correlation information of data. However, CNN is challenging to learn ...

"For the EstimatorQNN, the expected output shape for the forward pass is (1, num_qubits * num_observables)” In practice, the forward pass returns an array of shape (batch_size, num_observables)—one ...

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

In this study we focus on two subnetworks common in the circuitry of swim central pattern generators (CPGs) in the sea slugs, Melibe leonina and Dendronotus iris and show that they are independently ...

ABSTRACT: This paper examines the effectiveness of the Differential autoregressive integrated moving average (ARIMA) model in comparison to the Long Short Term Memory (LSTM) neural network model for ...

The intersection of neuroscience and artificial intelligence has seen remarkable progress, notably through the development of an open-source Python library known as “snnTorch.” This innovative code, ...

Deep learning neural networks, exemplified by models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Generative Adversarial Networks (GANs), have achieved remarkable ...