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Reinforcement Learning

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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/MIT-HAN-LAB/ProxylessNAS

HAQ: Hardware-Aware Automated Quantization with Mixed Precision

https://github.com/MLCS-Yonsei/ddpg-control

Continuous control with deep reinforcement learning

https://github.com/MLforHealth/rl_representations

Benchmarking Batch Deep Reinforcement Learning Algorithms

https://github.com/MOVzeroOne/DQN

Playing Atari with Deep Reinforcement Learning

https://github.com/MSRDL/Deep4Cast

Concrete Dropout

https://github.com/MUmarJaved/MultiAgent-Distributed-Reinforcement-Learning

Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning

https://github.com/MVerghese/NN-Dynamics-Sparse-Reward

Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning

https://github.com/MYPETFISH/PGPortfolio

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/MagaliDrumare/Augmented-Random-Search-ARS-Intuition

Simple random search provides a competitive approach to reinforcement learning

https://github.com/Mahoumaru/t-momentum

TAdam: A Robust Stochastic Gradient Optimizer

https://github.com/Maltimore/robotic_nanofabrication

Autonomous robotic nanofabrication with reinforcement learning

https://github.com/Manchery/iql-pytorch

Offline Reinforcement Learning with Implicit Q-Learning

https://github.com/ManooshSamiei/Object-Detection-Deep-Reinforcement-Learning

Object Detection with Deep Reinforcement Learning

https://github.com/MarSaKi/NvEM

Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments

https://github.com/MarcAntoineAlex/darts

DARTS: Differentiable Architecture Search

https://github.com/MarsEleven/car_racer_RL

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/MateuszJanda/netris-ai-robot

Playing Atari with Deep Reinforcement Learning

https://github.com/MathPhysSim/PER-NAF

Continuous control with deep reinforcement learning

https://github.com/MatheusMRFM/A3C-LSTM-with-Tensorflow

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/MattJud/gnn_jssp

Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning

https://github.com/MattKleinsmith/pbt

Population Based Training of Neural Networks

https://github.com/MatteoBrentegani/PPO

Proximal Policy Optimization Algorithms

https://github.com/MatthieuSarkis/Portfolio-Optimization-and-Goal-Based-Investment-with-Reinforcement-Learning

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

https://github.com/MaxHolmberg96/GradCAM

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/MaxSobolMark/HardRLWithYoutube

Playing hard exploration games by watching YouTube

https://github.com/MaximeBouton/AutomotiveSafeRL

Safe Reinforcement Learning with Scene Decomposition for Navigating Complex Urban Environments

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Deep_Reinforcement_Learning_with_Double_Q_learning

Deep Reinforcement Learning with Double Q-learning

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Model_Agnostic_Meta_Learning_for_Fast_Adaptation_of_Deep_Networks

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Playing_Atari_with_Deep_Reinforcement_Learning

Playing Atari with Deep Reinforcement Learning

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Proximal_Policy_Optimization_Algorithms

Proximal Policy Optimization Algorithms

https://github.com/MeRKeZ/DeepDrone_Airsim

Learning Visuomotor Policies for Aerial Navigation Using Cross-Modal Representations

https://github.com/Medabid1/Bayes-by-backprob

Weight Uncertainty in Neural Networks

https://github.com/Medabid1/CPC

Representation Learning with Contrastive Predictive Coding

https://github.com/Medabid1/RL_Project

Continuous control with deep reinforcement learning

https://github.com/MehdiChelh/Zoo

Weight Uncertainty in Neural Networks

https://github.com/MehmetBarutcu/Streaming-Algorithm-for-Monotone-k-Submodular-Maximization-with-Cardinality-Constraints

Playing Atari with Deep Reinforcement Learning

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.