Google’s Lang Extract uses prompts with Gemini or GPT, works locally or in the cloud, and helps you ship reliable, traceable data faster.

Abstract: This paper investigates the recovery of a node-domain sparse graph signal from the output of a graph filter. This problem, which is often referred to as the identification of the source of a ...

Abstract: Sparse graph signals have recently been utilized in graph signal processing (GSP) for tasks such as graph signal reconstruction, blind deconvolution, and sampling. In addition, sparse graph ...

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 ...

Navigability captures the ability of a complex network to support efficient, decentralized search. The concept has a rich history, from Milgram’s "six degrees of separation" to Kleinberg’s ...

There is a new sorting algorithm a deterministic O(m log2/3 n)-time algorithm for single-source shortest paths (SSSP) on directed graphs with real non-negative edge weights in the comparison-addition ...

STG-DMD (Sparse-Coded Time-Delay Graph Dynamic Mode Decomposition) is a data-driven framework for modeling nonlinear dynamics on graph structures. It integrates: StgDmd/ ├── code/ │ ├── artificial/ │ ...

Building a chatbot can feel like an overwhelming task, especially when you’re juggling multiple tools and trying to ensure everything works seamlessly. If you’ve ever found yourself stuck between ...

Knowledge graphs (KGs) are the foundation of artificial intelligence applications but are incomplete and sparse, affecting their effectiveness. Well-established KGs such as DBpedia and Wikidata lack ...