Popular GitHub repos like Microsoft’s “Generative AI for Beginners” and “LLMs from Scratch” teach modern AI concepts step by ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

AquaSentinel is a prototype designed to detect anomalous heart rates and blood oxygen levels of deep-sea divers, developed for the EYH university competition. AquaSentinel is a component of our ...

Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions, an essential aspect of solving partial differential ...

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 ...

Abstract: Activation functions are pivotal in neural networks, determining the output of each neuron. Traditionally, functions like sigmoid and ReLU have been static and deterministic. However, the ...

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research I have used a phenomenon called “quantum tunnelling” to ...