Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Abstract: This study introduces a novel strategy for waste segregation employing Convolutional Neural Networks (CNNs) and Python programming. By harnessing CNNs’ image feature extraction capabilities, ...

PythoC lets you use Python as a C code generator, but with more features and flexibility than Cython provides. Here’s a first look at the new C code generator for Python. Python and C share more than ...

A comprehensive implementation of a Variational Autoencoder (VAE) for unsupervised data generation with uncertainty quantification, featuring comparative analysis against deterministic baselines. This ...

This repository showcases **10 curated projects** that demonstrate the mathematics behind Artificial Neural Networks (ANNs) using practical Python implementations. Ideal for learners, researchers, and ...

The Boryviter Center of Research is developing a neural network for the passive collection and analysis of publications in enemy media resources. Pavlo Musienko, head of the analytical department, ...

Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland ...

With increasing model complexity, models are typically re-used and evolved rather than starting from scratch. There is also a growing challenge in ensuring that these models can seamlessly work across ...

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 ...