How a NPU programming model can boost the ability to port new models onto state-of-the-art embedded silicon.

Abstract: Rapid advancements of artificial neural networks for computer sciences, inspired by biological neuron interaction mechanisms, may be leveraged in reverse to synthetic biology by providing ...

Overview: NumPy is ideal for data analysis, scientific computing, and basic ML tasks.PyTorch excels in deep learning, GPU ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Set up the foundational structure for the machine learning module with core neural network types, tensor operations, and GPU acceleration support.

Abstract: This article is concerned with the proportional-integral-observer (PIO)-based fusion estimation problem for a class of artificial neural networks (ANNs) equipped with multiple sensors, which ...

Introduction: Exposure to teratogenic compounds during pregnancy can lead to significant birth defects. Given the considerable variation in drug responses across species, along with the financial and ...

In today's data-driven environment, Python has become the mainstream language in the fields of machine learning and data science due to its concise syntax, rich library support, and active community, ...

A high-performance Python package implementing the Quasi-Steady State (QSS) method for solving stiff ordinary differential equations, with particular focus on combustion chemistry applications. This ...