Papers with Code 아카이브

Reinforcement Learning

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평가표

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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/RasmusAndersen/grad-cam

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

https://github.com/RchalYang/Soft-Module

Multi-Task Reinforcement Learning with Soft Modularization

https://github.com/Recognito-Vision/Android-FaceRecognition-FaceLivenessDetection

Combinatorial Client-Master Multiagent Deep Reinforcement Learning for Task Offloading in Mobile Edge Computing

https://github.com/Remtasya/DDPG-Actor-Critic-Reinforcement-Learning-Reacher-Environment

Continuous control with deep reinforcement learning

https://github.com/RevanMacQueen/LearningFromHumans

ZPD Teaching Strategies for Deep Reinforcement Learning from Demonstrations

https://github.com/RexGLiu/rlpyt_crbp

Accelerated Methods for Deep Reinforcement Learning

https://github.com/RickyMexx/DeepRL-LTL

Modular Deep Reinforcement Learning with Temporal Logic Specifications

https://github.com/RickyMexx/DeepRL-LTLf

Modular Deep Reinforcement Learning with Temporal Logic Specifications

https://github.com/Ring367/A-Deep-Reinforcement-Learning-Network-for-Traffic-Light-Cycle-Control

Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks

https://github.com/Ring367/Double-Dueling-DQN-to-control-traffic-lights-on-SUMO

Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks

https://github.com/RingBDStack/DRL-DBSCAN/tree/main/DRL-DBSCAN-mindspore

Automating DBSCAN via Deep Reinforcement Learning

https://github.com/Rintarooo/TSP_DRL_PointerNet

Neural Combinatorial Optimization with Reinforcement Learning

https://github.com/Rintarooo/TSP_DRL_PtrNet

Neural Combinatorial Optimization with Reinforcement Learning

https://github.com/Rintarooo/TSP_RL_Pointer_Actor_Critic

Neural Combinatorial Optimization with Reinforcement Learning

https://github.com/Rishit-dagli/Visualize.AI

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

https://github.com/RobertKirk/roam-tools

Learning to Compose Neural Networks for Question Answering

https://github.com/Roberto09/Dynamic-Attention-Model-for-VRP---Pytorch

A Deep Reinforcement Learning Algorithm Using Dynamic Attention Model for Vehicle Routing Problems

https://github.com/RoblabWh/RobLearn

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

https://github.com/RobotMobile/rl-paper-review

Playing Atari with Deep Reinforcement Learning

https://github.com/RobvanGastel/meta-rl-algorithms

RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning

https://github.com/RojaImmanni/FlappyBird_using_RL

FlapAI Bird: Training an Agent to Play Flappy Bird Using Reinforcement Learning Techniques

https://github.com/Roman-Kozachek/TradeBot

Deep Reinforcement Learning with Double Q-learning

https://github.com/Rowing0914/Atari-Grand-Challenge-Processor

The Atari Grand Challenge Dataset

https://github.com/Rowing0914/gym_modified

OpenAI Gym

https://github.com/RuizhiZhang/MManGoCam

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

https://github.com/Runist/torch_maml

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

https://github.com/RunzheStat/TestMDP

Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making

https://github.com/RuoyuChen10/objectdetection-saliency-maps

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

https://github.com/Ryan-Ray-Martin/Market-Maker

Market-making with reinforcement-learning (SAC)

https://github.com/RyanKim17920/DeepMoE

Deep Mixture of Experts via Shallow Embedding

https://github.com/RyanRizzo96/gym-FetchCustom

OpenAI Gym

https://github.com/SAGNIKMJR/CODEBRIM_MetaQNN

Meta-learning Convolutional Neural Architectures for Multi-target Concrete Defect Classification with the COncrete DEfect BRidge IMage Dataset

https://github.com/SAGNIKMJR/MetaQNN_ImageClassification_PyTorch

Designing Neural Network Architectures using Reinforcement Learning

https://github.com/SAGNIKMJR/MetaQNN_ImageGenerationGAN_DiscriminatorFixed_PyTorch

Designing Neural Network Architectures using Reinforcement Learning

https://github.com/SAGNIKMJR/MetaQNN_ImageGenerationVCAE_PyTorch

Designing Neural Network Architectures using Reinforcement Learning

https://github.com/SJTU-VLG/ImageCaption-LBPF-qy

Self-critical Sequence Training for Image Captioning

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