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Antonin Raffin

Research Engineer in Robotics and Machine Learning

German Aerospace Center (DLR)

Bio

Robots. Machine Learning. Blues Dance.

Interests

  • Robotics
  • Reinforcement Learning
  • State Representation Learning
  • Machine Learning

Projects

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SBX: Stable Baselines Jax

Proof of concept version of Stable-Baselines3 in Jax.

Datasaurust

Blazingly fast implementation of the Datasaurus paper in Rust. Same Stats, Different Graphs.

Stable Baselines3

A set of improved implementations of reinforcement learning algorithms in PyTorch.

Learning to Drive Smoothly in Minutes

Learning to drive smoothly in minutes using reinforcement learning on a Donkey Car.

RL Baselines Zoo

A collection of 70+ pre-trained RL agents using Stable Baselines

S-RL Toolbox

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

Stable Baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

Racing Robot

Autonomous Racing Robot With an Arduino, a Raspberry Pi and a Pi Camera

Arduino Robust Serial

A simple and robust serial communication protocol. Implementation in C Arduino, C++, Python and Rust.

Recent & Upcoming Talks

Ingredients for Learning Locomotion Directly on Real Hardware

Invited talk for the Soccer Robots workshop at Humanoids conference 2024

Designing and Running Real-World RL Experiments

Talk at the Reinforcement Learning for Autonomous Accelerators workshop (RL4AA). The idea is to walk through the different steps of RL experimentation (task design, choosing the right algorithm, implementing safety layers) and also provide practical advice on how to run experiments and troubleshoot common problems.

Practical Tips for Reliable Reinforcement Learning

Talk at the CDC 2023 Workshop on Benchmarking, Reproducibility, and Open-Source Code in Controls, about the lessons learned while developping Stable-Baselines3 to have reliable implementations and reproducible experiments.

Experience

 
 
 
 
 

Researcher

German Aerospace Center (DLR)

October 2018 – Present Munich
Machine Learning for Robots.
 
 
 
 
 

Research Engineer

ENSTA ParisTech - U2IS robotics lab

October 2017 – October 2018 Palaiseau
Working on Reinforcement Learning and State Representation Learning for the DREAM project.
 
 
 
 
 

Research Intern

Riminder

April 2017 – September 2017 Paris
Deep Learning for Human Resources.
 
 
 
 
 

Research Intern

TU Berlin - RBO lab

May 2016 – August 2016 Berlin
Research internship in representation and reinforcement learning.

Recent Posts

Automatic Hyperparameter Tuning - A Visual Guide (Part 1)

When you’re building a machine learning model, you want to find the best hyperparameters to make it shine. But who has the luxury of trying out every possible combination? The good news is that automatic hyperparameter tuning can save the day.

Rliable: Better Evaluation for Reinforcement Learning - A Visual Explanation

It is critical for Reinforcement Learning (RL) practitioners to properly evaluate and compare results. Reporting results with poor comparison leads to a progress mirage and may underestimate the stochasticity of the results.

Stable-Baselines3: Reliable Reinforcement Learning Implementations

After several months of beta, we are happy to announce the release of Stable-Baselines3 (SB3) v1.0, a set of reliable implementations of reinforcement learning (RL) algorithms in PyTorch =D! It is the next major version of Stable Baselines.

Learning to Drive Smoothly in Minutes

Learning to drive smoothly in minutes using reinforcement learning on a Donkey Car.