Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Dive into Faraday’s Law of Electromagnetic Induction with a practical Python implementation in this first part of our Electrodynamics series. Learn how to simulate and visualize changing magnetic ...

Abstract: Spatial Crowdsourcing (SC) has emerged as a significant paradigm for executing complex real-world projects and tasks, which are often decomposed into interdependent subtasks requiring ...

Take your physics and coding skills to the next level with **“Learn To Calculate Launch Angles In Projectile Motion Using Python.”** This tutorial combines the fundamentals of projectile motion with ...

verl is a flexible, efficient and production-ready RL training library for large language models (LLMs). verl is the open-source version of HybridFlow: A Flexible and Efficient RLHF Framework paper.

Recently, there have been significant research interests in training large language models (LLMs) with reinforcement learning (RL) on real-world tasks, such as multi-turn code generation. While online ...

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: The problem of multiagent encirclement with multiobstacle collision avoidance (EMOCA) has been challenging since it is difficult to balance the tradeoff between surrounding a mobile target ...

AI can be used to produce clinically meaningful radiology reports using medical images like chest x-rays. Medical image report generation can reduce reporting burden while improving workflow ...