Abstract: Context: The greater number of code smells can make the software system hard to maintain. Code smell indicates the problems which can reduce the software quality. It is the area within the ...

In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building reinforcement learning algorithms with JAX. We combine ...

Learn about DenseNet, one of the most powerful deep learning architectures, in this beginner-friendly tutorial. Understand its structure, advantages, and how it’s used in real-world AI applications.

Learn how to effectively read and understand deep learning code with this beginner-friendly guide. Break down complex scripts and get comfortable navigating AI projects step by step. #DeepLearning ...

The ongoing revolution in deep learning is reshaping research across many fields, including economics. Its effects are especially clear in solving dynamic economic models. These models often lack ...

Abstract: This research basically explores the analysis and modelling of deep learning techniques. Advanced AI is being integrated and to automate the flowchart-to-code generation process, vision ...

This Collection calls for submissions of original research into techniques that facilitate the advancement of deep learning for image analysis and object detection, driving computer vision forward and ...

Objectives: Gain hands-on, code-first experience with deep learning theories, models, and skills that are useful for applications and for advancing science. We focus on how to decide which problems ...

Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code remains underexplored. Due to the size and complexities of ...

Russia’s intelligence services turned Brazil into an assembly line for deep-cover operatives. A team of federal agents from the South American country has been quietly dismantling it. By Michael ...

A research team has developed a groundbreaking deep learning-based method for analyzing the cytoskeleton -- the structural framework inside cells -- more accurately and efficiently than ever before.