Papers with Code 아카이브

Reinforcement Learning

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보존된 평가 기록

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코드

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

https://github.com/xaviercanche/Grad-CAM

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

https://github.com/xavierchanglingli/regularized-optimal-experience-replay

An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay

https://github.com/xbpeng/DeepMimic

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

https://github.com/xbpeng/awr

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

https://github.com/xgfelicia/Reinforcement-Learning

Deep Reinforcement Learning with Double Q-learning

https://github.com/xgfelicia/SRVRPG

Sample Efficient Policy Gradient Methods with Recursive Variance Reduction

https://github.com/xiangyu-liu/Computer-Network

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks

https://github.com/xiaobai714/image_caption

Self-critical Sequence Training for Image Captioning

https://github.com/xiaojunxu/SQLNet

Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

https://github.com/xiaomi-automl/FALSR

Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search

https://github.com/xiawenwen49/ppo

Proximal Policy Optimization Algorithms

https://github.com/xiayuyang/AUTO

Parameterized Decision-making with Multi-modal Perception for Autonomous Driving

https://github.com/xiexiexiaoxiexie/Udacity-self-driving-car-engineer-P7-Highway-Driving

DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation

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

Learning to Manipulate Deformable Objects without Demonstrations

https://github.com/xinjinghao/sparrow-v1

Prioritized Experience Replay

https://github.com/xionghuichen/maple

NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning

https://github.com/xiusu/ViTAS

AutoSlim: Towards One-Shot Architecture Search for Channel Numbers

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

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

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

Playing Atari with Deep Reinforcement Learning

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

The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games

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

Proximal Policy Optimization Algorithms

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

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

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/xkotaro/lockdowneR

Optimising Lockdown Policies for Epidemic Control using Reinforcement Learning

https://github.com/xlrshop/Parl

ParlAI: A Dialog Research Software Platform

https://github.com/xn1997/pytorch-grad-cam

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

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

Continuous control with deep reinforcement learning

https://github.com/xuanhungho/nsga

Regularized Evolution for Image Classifier Architecture Search

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

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

https://github.com/xuezeyue/dancegrpo

DanceGRPO: Unleashing GRPO on Visual Generation

https://github.com/xujinfan/Reinforced-Continual-Learning

Reinforced Continual Learning

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

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

https://github.com/xusophia/DataSciFinalProj

Prioritized Experience Replay

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/xuzijian629/combopt-zero

Solving NP-Hard Problems on Graphs with Extended AlphaGo Zero

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