Welcome to FSLR's news and media gallery section. Visit this section often for all the latest about FSLR's and other Sainte Rose de Lima's activities and events. In 2024, Sainte de Rose Lima turns 160 years old. Click HERE to see how you can participate in this memorable milestone! TOGETHER, WE CAN ACCOMPLISH ANYTHING!

Actively supporting many education projects in Haiti since 2006. Help us continue! Donate TODAY!

Here you will find links to galleries of all FSRL recent and past events. We hope you'll join us at our next events supporting FSRL activities in Haiti. Most recent event: FSRL organized a fundraising cocktail in Pembroke Pines Florida on 4/24/18

Fondée avec la vision de transformer les soins de réhabilitation en Haïti, la Faculté des Sciences de Réhabilitation de Léogâne (FSRL) incarne l’excellence et l’innovation dans l’éducation spécialisée.

Find the Faculté des Sciences de Réhabilitation de Léogâne style guide with brand assets such as logos, colors, fonts, and more.

The FSRL (Fast Safe Reinforcement Learning) package contains modularized implementations of safe RL algorithms based on PyTorch and the Tianshou framework [Weng et al., 2022]. The implemented safe RL algorithms include:

The Fast Safe Reinforcement Learning (FSRL) package provides modularized implementations of Safe RL algorithms based on PyTorch and the Tianshou framework. Safe RL is a rapidly evolving subfield of RL, focusing on ensuring the safety of learning agents during the training and deployment process.

Foundation Sainte Rose de Lima, P.O. Box 881036. 834 likes · 1 talking about this. FSRL was founded in 2006 in Florida to support SRL's and its projects....

Haiti Rehabilitation Foundation (HRF) is a non-profit, 501c3 organization founded with the mission of educating Haitians in the art and science of Physical and Occupational Therapy. For those that want to help Haiti in a lasting way, FSRL is a homerun; it is an efficient way to spend time and money as the work it is doing will endure.

2024年9月13日 · FSRL （Fast Safe Reinforcement Learning）是一个基于PyTorch和 Tianshou 框架的模块化安全强化学习（Safe RL）算法实现包。 安全强化学习是强化学习领域中一个快速发展的子领域，专注于在训练和部署过程中确保学习代理的安全性。 FSRL项目旨在提供高质量、快速的Safe RL算法实现，为研究人员和开发者提供一个理想的起点，以探索和实验这一重要领域。 FSRL的核心技术优势在于其模块化设计和高效的算法实现： 高质量实现：FSRL的算法实现 …