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Hi, I’m Edan, and I’m passionate about advancing the field of reinforcement learning through open-source projects. I created Stoix to provide researchers with an efficient, JAX-based framework that simplifies RL experimentation while maximizing performance. Your sponsorship helps me continue improving Stoix, adding new features, and ensuring it stays a valuable tool for the community. By supporting my work, you’re helping make cutting-edge RL research more accessible and efficient for everyone. Thank you!
Featured work
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EdanToledo/Stoix
🏛️A research-friendly codebase for fast experimentation of single-agent reinforcement learning in JAX • End-to-End JAX RL
Python 241 -
instadeepai/flashbax
⚡ Flashbax: Accelerated Replay Buffers in JAX
Python 214