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/ugo-nama-kun/gym_torcs

Simulated Car Racing Championship: Competition Software Manual

https://github.com/unstablecursor/robotino_rl

Deep Reinforcement learning for real autonomous mobile robot navigation in indoor environments

https://github.com/uoe-agents/derl

#Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning

https://github.com/uvipen/super-mario-bros-ppo-pytorch

Proximal Policy Optimization Algorithms

https://github.com/vaibhavsaxena11/cwvae

Learning Latent Dynamics for Planning from Pixels

https://github.com/varuncs2011/rl

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/vcadillog/PPO-Mario-Bros-Tensorflow-2

Proximal Policy Optimization Algorithms

https://github.com/vermashresth/damage-aware-PPO

Proximal Policy Optimization Algorithms

https://github.com/vgudapati/DRLND_Collaboration_Competetion

Distributed Distributional Deterministic Policy Gradients

https://github.com/vheuthe/microbot_rl

Proximal Policy Optimization Algorithms

https://github.com/voot-t/ril_co

Robust Imitation Learning from Noisy Demonstrations

https://github.com/vu-resilient-distributed-systems/assignment-1-fall-19

Simulated Car Racing Championship: Competition Software Manual

https://github.com/vub-ai-lab/qwr

Q-Value Weighted Regression: Reinforcement Learning with Limited Data

https://github.com/vvanirudh/imitation-learning-gym

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

https://github.com/wangshub/RL-Stock

Proximal Policy Optimization Algorithms

https://github.com/wangzhengfei0730/NIPS2018-AIforProsthetics

Proximal Policy Optimization Algorithms

https://github.com/wassname/rl-portfolio-management

Continuous control with deep reinforcement learning

https://github.com/watchernyu/spinningup-drl-prototyping

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

https://github.com/willwhitney/dynamics-aware-embeddings

Dynamics-aware Embeddings

https://github.com/wpiszlogin/driver_critic

Continuous control with deep reinforcement learning

https://github.com/wwydmanski/rl_tennis

Continuous control with deep reinforcement learning

https://github.com/wyndwarrior/imitation_from_observation

Benchmarking Deep Reinforcement Learning for Continuous Control

https://github.com/xbpeng/awr

Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

https://github.com/xiawenwen49/ppo

Proximal Policy Optimization Algorithms

https://github.com/xingyu-lin/softagent

Learning Latent Dynamics for Planning from Pixels

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

Proximal Policy Optimization Algorithms

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/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/xyshadow/baseline_ddpg

Continuous control with deep reinforcement learning

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

Real-Time Reinforcement Learning

https://github.com/yannbouteiller/rtgym

Reinforcement Learning with Random Delays

https://github.com/yfeng95/deca

Learning an Animatable Detailed 3D Face Model from In-The-Wild Images

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

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

https://github.com/yifan12wu/td3-jax

Addressing Function Approximation Error in Actor-Critic Methods

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