The editorial, "Dynamics-driven medical big data mining: dynamic approaches to early disease forecasting and individualized care," published in Intelligent Medicine (February 2026, Volume 6, Issue 1), ...

Google Gemini has gained interactive visualization capabilities, letting users build 3D models, physics simulations, and adjustable charts directly in chat.

Google has launched TorchTPU, an engineering stack enabling PyTorch workloads to run natively on TPU infrastructure for ...

A research team led by Potsdam-based bioinformatician Prof. Dr. Zoran Nikoloski has developed a computational approach and an ...

A research team led by Potsdam-based bioinformatician Prof. Dr Zoran Nikoloski has developed a computational approach and an accompanying tool that enables the detailed analysis and reconstruction of ...

In this tutorial, we build a hierarchical planner agent using an open-source instruct model. We design a structured multi-agent architecture comprising a planner agent, an executor agent, and an ...

Explore the power of interactive physics visualizations with animated graphs using VPython and GlowScript for dynamic simulations! This guide demonstrates how to create real-time animated graphs that ...

Explore core physics concepts and graphing techniques in Python Physics Lesson 3! In this tutorial, we show you how to use Python to visualize physical phenomena, analyze data, and better understand ...

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 ...

DART addresses two critical limitations in existing stock market prediction systems. First, most graph-based approaches rely on static knowledge graphs that fail to capture the dynamic nature of ...

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, ...