Dive into Faraday’s Law of Electromagnetic Induction with a practical Python implementation in this first part of our Electrodynamics series. Learn how to simulate and visualize changing magnetic ...

Our DiET-GS++ enables high quality novel-view synthesis with recovering precise color and well-defined details from the blurry multi-view images. [2025/02/27] DiET-GS is accepted to CVPR 2025 🔥. The ...

Abstract: 3D Scene Graphs integrate both metric and semantic information, yet their structure remains underexploited for improving path planning efficiency and interpretability. In this work, we ...

ABSTRACT: Since about 1970, Geographic Information Systems (GISs) have been implemented as a tool to organize spatial data related to locations on or near the surface of the Earth. As technology ...

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 ...

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 ...

QR codes are quickly replacing the traditional barcode as the new essential tool shaping modern retail. A decade ago, they were just a simple way to connect in-store and online shopping, but now they ...

ICC’s Ryan Colker explains how thoughtful code development and evaluation processes are paving the way for safe, scalable adoption of next-generation building technologies. ICC's Ryan Colker speaks at ...

Styl3R predicts stylized 3D Gaussians in less than a second using a feed-forward network given unposed sparse-view images and an arbitrary style image. 🤖 Our method could potentially improve the ...

Learning Python often begins with a simple yet powerful exercise: printing “Hello, World!” to the screen. This one-liner doesn’t just display text—it’s your first step toward mastering Python ...

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, ...