An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

For more than eighty years, deep learning has relied on a simplified model of brain function. Now, a Pittsburgh startup ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. EncoderMap is a dimensionality reduction method that is tailored for the analysis of ...

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...

1 Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan 2 Graduate School of Engineering, The University of Tokyo, Tokyo, Japan Neural oscillation, particularly gamma oscillation ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...