Papers with Code 아카이브

3D Face Modelling

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코드

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

https://github.com/Gouet/DDPG_PendulumV1

Continuous control with deep reinforcement learning

https://github.com/Gouet/PPO-gym

Proximal Policy Optimization Algorithms

https://github.com/Gouet/PPO-pytorch

Proximal Policy Optimization Algorithms

https://github.com/Gregory-Eales/proximal-policy-optimization

Proximal Policy Optimization Algorithms

https://github.com/HardikJ7321/AugmentedRandomSearch-AI-

Simple random search provides a competitive approach to reinforcement learning

https://github.com/Hikaylee/SynergyNet

Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

https://github.com/HzcIrving/DLRL-PlayGround

Distributed Distributional Deterministic Policy Gradients

https://github.com/HzcIrving/DLRL-PlayGround/tree/main/Offline%20RL/BCQ

Off-Policy Deep Reinforcement Learning without Exploration

https://github.com/InSpaceAI/RL-Zoo

Continuous control with deep reinforcement learning

https://github.com/Ipsedo/EvoMotion

Proximal Policy Optimization Algorithms

https://github.com/Itomigna2/Muesli-lunarlander

Muesli: Combining Improvements in Policy Optimization

https://github.com/IvanVigor/Deep-Deterministic-Policy-Gradient-Unity-Env

Continuous control with deep reinforcement learning

https://github.com/IvanVigor/MADDPG-Unity

Continuous control with deep reinforcement learning

https://github.com/J93T/TP4-DDPG

Continuous control with deep reinforcement learning

https://github.com/JL321/Proximal-Policy-Optimization

Proximal Policy Optimization Algorithms

https://github.com/JL321/mujo-2DHalf-Cheetah

Continuous control with deep reinforcement learning

https://github.com/JL321/mujo-2DWalker

Continuous control with deep reinforcement learning

https://github.com/Ji4chenLi/ARS_experiment

Simple random search provides a competitive approach to reinforcement learning

https://github.com/Jingliang-Duan/Distributional-Soft-Actor-Critic

Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors

https://github.com/JohannesAck/MATD3implementation

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/JonasRSV/DDPG

Continuous control with deep reinforcement learning

https://github.com/JonasRSV/DQNTensorflow

Parameter Space Noise for Exploration

https://github.com/JonasRSV/PGTensorflow

Continuous control with deep reinforcement learning

https://github.com/JonasRSV/PPO

High-Dimensional Continuous Control Using Generalized Advantage Estimation

https://github.com/JorgeA-RD/Reinforcement-Learning-Agents/tree/main/DDPG

Continuous control with deep reinforcement learning

https://github.com/KAIST-AILab/deeprl_practice_colab

Continuous control with deep reinforcement learning

https://github.com/Kaixhin/ACER

Sample Efficient Actor-Critic with Experience Replay

https://github.com/Kaixhin/PlaNet

Learning Latent Dynamics for Planning from Pixels

https://github.com/Kaixhin/imitation-learning

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

https://github.com/Kaixhin/spinning-up-basic

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

https://github.com/KarlXing/RL-Visual-Continuous-Control

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

https://github.com/KelvinYang0320/deepbots-panda

Continuous control with deep reinforcement learning

https://github.com/Khrylx/PyTorch-RL

Proximal Policy Optimization Algorithms

https://github.com/Kikumu/Reinforcement-Learning-repo

Continuous control with deep reinforcement learning

https://github.com/KohMat/carracing-dreamer

Dream to Control: Learning Behaviors by Latent Imagination

https://github.com/LM095/DDPG-implementation

Continuous control with deep reinforcement learning

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