Papers with Code 아카이브

Deep Reinforcement Learning

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

https://github.com/xiuyu0000/new_papers_codes/tree/main/sac

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

https://github.com/xtma/simple-pytorch-rl

Continuous control with deep reinforcement learning

https://github.com/xuehy/pytorch-maddpg

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/xukaidi13/Simulation-code

Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet

https://github.com/xusophia/DataSciFinalProj

Dueling Network Architectures for Deep Reinforcement Learning

https://github.com/xuyuandong/simple-ddpg

Continuous control with deep reinforcement learning

https://github.com/xuzhiyuan1528/KTM-DRL

Knowledge Transfer in Multi-Task Deep Reinforcement Learning for Continuous Control

https://github.com/xxkkrr/conv_rec_sys

Conversational Recommender System

https://github.com/xyshadow/baseline_ddpg

Continuous control with deep reinforcement learning

https://github.com/xzxzxzxz/interp

Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

https://github.com/yangyucheng000/deepbsde

Solving high-dimensional partial differential equations using deep learning

https://github.com/yannbouteiller/gym-airsimdroneracinglab

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

https://github.com/yaringal/DropoutUncertaintyExps

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

https://github.com/yaxinchen666/dce_pricingRL

Playing Atari with Deep Reinforcement Learning

https://github.com/yhisaki/average-reward-drl

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

https://github.com/yifan-you-37/omnihang

OmniHang: Learning to Hang Arbitrary Objects using Contact Point Correspondences and Neural Collision Estimation

https://github.com/yifan123/arxiv_spider

Uniformly Conservative Exploration in Reinforcement Learning

https://github.com/yiliu1/Machine-Learning-in-Finance

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

https://github.com/yimingpeng/sac-master

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

https://github.com/yining043/SAC-discrete

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

https://github.com/yining043/TSP-improve

Learning Improvement Heuristics for Solving Routing Problems

https://github.com/ymlwww/rlproject

Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward

https://github.com/yongsukyee/uncertain_blackholemass

A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification

https://github.com/yoojungsun0/Psych239

Model-Free Episodic Control

https://github.com/younggyoseo/RE3

State Entropy Maximization with Random Encoders for Efficient Exploration

https://github.com/yuanming-hu/exposure

Exposure: A White-Box Photo Post-Processing Framework

https://github.com/yuchaoch/project/tree/main/Collaborative_Multi_BS_Power_Management_for_Dense_Radio_Access_Network_using_Deep_Reinforcement_Learning

Collaborative Multi-BS Power Management for Dense Radio Access Network using Deep Reinforcement Learning

https://github.com/yufeiwang63/L2D-learning-to-discretize

Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement Learning

https://github.com/yuke93/RL-Restore

Crafting a Toolchain for Image Restoration by Deep Reinforcement Learning

https://github.com/yukezhu/tensorflow-reinforce

Continuous control with deep reinforcement learning

https://github.com/yusme/DDPG

Continuous control with deep reinforcement learning

https://github.com/yusukeurakami/slac-playground

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

https://github.com/ywchao/merel-mocap-gail

Learning human behaviors from motion capture by adversarial imitation

https://github.com/yytyvonne/DQN_agent_Chatbot

Deep Reinforcement Learning for Conversational AI

https://github.com/yzheng51/rl-dino-run

Deep Reinforcement Learning with Double Q-learning

https://github.com/zanghyu/offline_bisimulation

MICo: Improved representations via sampling-based state similarity for Markov decision processes

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