carlosluis

carlosluis's Stars

• isocpp/CppCoreGuidelines

  The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

  Language:CSS42.6k2k1.2k5.4k

• dennybritz/reinforcement-learning

  Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

  Language:Jupyter Notebook20.5k8591556k

• ShangtongZhang/reinforcement-learning-an-introduction

  Python Implementation of Reinforcement Learning: An Introduction

  Language:Python13.5k555994.8k

• karpathy/nn-zero-to-hero

  Neural Networks: Zero to Hero

  Language:Jupyter Notebook11.6k286311.5k

• madd86/awesome-system-design

  A curated list of awesome System Design (A.K.A. Distributed Systems) resources.

  9.5k19551.1k

• p-christ/Deep-Reinforcement-Learning-Algorithms-with-PyTorch

  PyTorch implementations of deep reinforcement learning algorithms and environments

  Language:Python5.6k106711.2k

• seungeunrho/minimalRL

  Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

  Language:Python2.8k4940460

• facebookresearch/hiplot

  HiPlot makes understanding high dimensional data easy

  Language:TypeScript2.7k2889140

• ros-navigation/navigation2

  ROS 2 Navigation Framework and System

  Language:C++2.5k642k1.3k

• HugoMatilla/Effective-JAVA-Summary

  Summary of the book Effective Java 2nd Edition by Joshua Bloch

  1.5k463405

• takuseno/d3rlpy

  An offline deep reinforcement learning library

  Language:Python1.3k27342232

• PufferAI/PufferLib

  Simplifying reinforcement learning for complex game environments

  Language:Python1.1k51043

• tinkoff-ai/CORL

  High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

  Language:Python1.1k1628124

• clvrai/awesome-rl-envs

  1k31479

• facebookresearch/mbrl-lib

  Library for Model Based RL

  Language:Python9552567155

• luchris429/purejaxrl

  Really Fast End-to-End Jax RL Implementations

  Language:Python678112256

• qpsolvers/qpsolvers

  Quadratic programming solvers in Python with a unified API

  Language:Python582159986

• david-sauvage/effective-java-summary

  A personnal summary of the book Effective Java by Joshua Bloch

  26013068

• madplotlib/madplotlib

  A C++ wrapper of Qt Charts that looks, tastes and smells like matplotlib but isn't.

  Language:C++25311246

• openrlbenchmark/openrlbenchmark

  Language:Python192769

• corl-team/xland-minigrid

  JAX-accelerated Meta-Reinforcement Learning Environments Inspired by XLand and MiniGrid 🏎️

  Language:Python18991515

• UT-Austin-RPL/amago

  a simple and scalable agent for training adaptive policies with sequence-based RL

  Language:Python80154

• johnryan465/pscan

  Language:Python35112

• zdhNarsil/Stochastic-Marginal-Actor-Critic

  Official pytorch implementation for our ICLR 2023 paper "Latent State Marginalization as a Low-cost Approach for Improving Exploration".

  Language:Python24101

• stratisMarkou/sample-efficient-bayesian-rl

  Source for the sample efficient tabular RL submission to the 2019 NIPS workshop on Biological and Artificial RL

  Language:Jupyter Notebook223014

• yobibyte/unitary-scalarization-dmtl

  In Defense of the Unitary Scalarization for Deep Multi-Task Learning

  Language:Python21333

• mikehamer/swarm-trajectories

  Source code for the paper "Fast generation of collision-free trajectories for robot swarms using GPU acceleration"

  Language:Python18122

• boschresearch/ube-mbrl

  Model-Based Uncertainty in Value Functions (AISTATS2023)

  Language:Python1540

• ALRhub/MTS3

  Implementation of Neurips 2023 Paper "Multi Time Scale World Models"

  Language:Python691

• baskinburak/mrtrajreplan-dars2018

  Language:C++6318