InfoWorld

Pick your Python accelerator

With lazy imports, JIT compilation, Python-generated C, or the Python-esque Mojo, it has never been easier to make Python go ...
GitHub

Introduction to artificial neural networks in Python

This repository is a fork from https://github.com/carpentries-incubator/machine-learning-neural-python, an excellent introduction to ML for images. This half-day ...
How-To Geek on MSN

These 7 Python libraries are useful even if you're not a developer

Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.
IEEE

A Review of Uncertainty Representation and Quantification in Neural Networks

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

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...