Abstract: Deep learning (DL) has been widely applied in wireless communications to address diverse challenges, such as beam management, positioning, and channel state information (CSI) feedback.

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Kjell Bjørgeengen, Keith Rowe and John Tilbury are three central figures in contemporary experimental music, each with a trajectory that has helped redefine adjacent fields. Bjørgeengen, a Norwegian ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Abstract: Effectively estimating the uncertainty attached to neural network predictions thus becomes essential to improve robustness, reliability, and trustworthiness. This paper provides an overview ...

While the project includes an initial XOR experiment to build intuition, this documentation focuses solely on the more complex MNIST experiment. Much of the mathematical insight was drawn from the ...

This is my journey to implement NNs from first principles, one neuron at a time. In this notebook we build a neural network with 2 neurons in layer 1, and 1 neuron in layer 2. We then visualize how it ...