kohlerhector Goto Github PK
Name: Hector Kohler
Type: User
Company: INRIA
Bio: PhD Student in Interpretable Reinforcement Learning PhD @ Inria/CNRS/Univ. Lille
Twitter: kohler_hector
Location: Lille
Name: Hector Kohler
Type: User
Company: INRIA
Bio: PhD Student in Interpretable Reinforcement Learning PhD @ Inria/CNRS/Univ. Lille
Twitter: kohler_hector
Location: Lille
A simple implementation of Auto-Encoding Inverse Reinforcement Learning with PyTorch
Asymmetric methods for partially observable reinforcement learning
Comparing learning algorithms based on constraints (in progress).
Sequential Decision Making in Central, based on RLSS 2019
Simple library based on https://github.com/osigaud/Basic-Policy-Gradient-Labs made for the Master's project: Comparison of Evolutionnary Methods and Reinforcement Learning methods on classical control benchmarks. Supervised by Prof Olivier Sigaud with Damien Legros.
A simple time series forecasting library using RNNs
Simple continuous-states mdp generator for which the optimal policy is a decision tree of given depth. Interface with openAI Gym.
A small library to study some Covariance Matrix Estimators in R. Designed in 2019 as part of my Bachelor's Degree thesis.
Using Stable-Baselines 3 library to train a LunarLander-v2 agent. With Yannis Elrharbi-Fleury : https://github.com/sohio92
Trying MarioNette on Pong
Code image classification of MNIST dataset using different architectures: simple linear NN, autoencoder, and highway network
Code and PDF report about reproducing the Morris Pool experiment: model rats behaviour in a pool using reinforcement learning
PLS algo for knapsack problem.
Predicting prime numbers as list of bits.
Implementation of Dyna-Q according to Sutton and Barto. Implementation of Mattar's learning model: https://www.nature.com/articles/s41593-018-0232-z
An easy-to-use reinforcement learning library for research and education.
A gymnasium wrapper for objects states detected with the Segment Anything Model.
Some exercises for the class of Reinforcement Learning at University of Lille
Study Model-Based Policy Optimization by varying the model estimator classes (e.g Decision Trees vs MLP)
Using Tree estimators of the MDP models to then count leaves grouping similar transitions and do count-based exploration.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.