Design intelligent AI agents with retrieval-augmented generation, memory components, and graph-based context integration.

Abstract: Large Language Models (LLMs) excel at general-purpose reasoning by leveraging broad commonsense knowledge, but they remain limited in tasks requiring personalized reasoning over ...

Python 3.10.13 PyTorch 1.13.0 torch_geometric 2.5.2 torch-cluster 1.6.1 torch-scatter 2.1.1 torch-sparse 0.6.17 torch-spline-conv 1.2.2 sparsemax 0.1.9 CUDA 11.7 Train RIGSL using the MELD dataset.

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, explains how it builds on Adam with Nesterov momentum, and shows you how to ...

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 ...

Hey! I noticed that the repo doesn’t yet have Dijkstra’s Algorithm, which is super useful for finding the shortest path in weighted graphs. I’d love to add it. Here’s what I plan to do: Implement ...

Genomic medicine relies on single reference genomes that miss crucial genetic diversity, creating diagnostic gaps that disproportionately affect underrepresented populations. Pangenome graphs, ...

In this tutorial, we explore how to leverage the PyBEL ecosystem to construct and analyze rich biological knowledge graphs directly within Google Colab. We begin by installing all necessary packages, ...

In this tutorial, we provide a practical guide for implementing LangGraph, a streamlined, graph-based AI orchestration framework, integrated seamlessly with Anthropic’s Claude API. Through detailed, ...

Hello there! 👋 I'm Luca, a BI Developer with a passion for all things data, Proficient in Python, SQL and Power BI ...

ABSTRACT: The flow of electrically conducting fluids is vital in engineering applications such as Magneto-hydro-dynamic (MHD) generators, Fusion reactors, cooling systems, and Geo-physics. In this ...