Deep Learning with Yacine on MSN

Nadam Optimizer From Scratch in Python – Step-by-Step Tutorial

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...
GitHub

The easiest way to build apps from your Python code

This project is no longer actively maintained. While the code remains available for reference and use, no updates, bug fixes, or new features will be provided. Users are encouraged to seek alternative ...
GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
IEEE

The Improved RRT Integrated With the Artificial Potential Field Path Planning Algorithm

Abstract: The traditional informed rapidly exploring random tree * algorithm (IRRT*) has several drawbacks, including low efficiency, numerous ineffective samples, strict requirements of the ...
IEEE

A Dual-Strategy Optimized JP - RRT Algorithm Based on Jump Point Sampling : Exploring Efficiency and Stability Enhancement in Robotic Path Planning

Abstract: This paper addresses low-efficiency and high-randomness node sampling in RRT - Connect for path planning by proposing a quadratic optimization JP - RRT algorithm using jump point sampling.