Turn Excel into a lightweight data-science tool for cleaning datasets, standardizing dates, visualizing clusters, and ...

This repository contains the official PyTorch implementation and the UMC4/12 Dataset for the paper: [UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate ...

Abstract: Graph neural networks (GNNs) have demonstrated significant success in solving real-world problems using both static and dynamic graph data. While static graphs remain constant, dynamic ...

What emerges is a portrait of Stanton not as a paragon of feminism but as a deeply peculiar person—one whose combination of vision and hubris happened to change history. This collection of thirteen ...

The Biden administration grappled with research suggesting natural immunity was more effective than COVID-19 vaccination shortly before federal vaccine mandates in 2021, admitting the rigor of the ...

Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

Minimalist plotting for Python, inspired by Edward Tufte’s principles of data visualization. Maximising the data–ink ratio: remove non-essential lines, marks, and colours. Content-driven spines and ...

In this comprehensive tutorial, we explore building an advanced, interactive dashboard with Taipy. Taipy is an innovative framework designed to create dynamic data-driven applications effortlessly.

Directed graphs and their afferent/efferent capacities are produced by Markov modeling of the universal cover of undirected graphs simultaneously with the calculation of volume entropy. Using these ...