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 ...
GitHub

GET-Zero: Graph Embodiment Transformer for Zero-shot Embodiment Generalization

This paper introduces GET-Zero, a model architecture and training procedure for learning an embodiment-aware control policy that can immediately adapt to new hardware changes without retraining. To do ...
Hosted on MSN

Photoshop CC 2018: Create Beautiful Mandalas & Spirographs using Variable Radial Symmetry.

This tutorial is for Photoshop version CC 2018 and later. Photoshop CC 2018 tutorial showing the “Variable Radial Symmetry” feature, which allows you to create beautiful spirographs and mandalas with ...
IEEE

Enhancing Adaptive Test Healing with Graph Neural Networks for Dependency-Aware Decision Making

Abstract: Flaky tests are a major obstacle in modern CI/CD pipelines, leading to unreliable feedback, increased reruns, and developer frustration. Our previously published adaptive healing framework ...