Papers with Code 아카이브

Reinforcement Learning

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코드

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

https://github.com/Neuraxio/Neuraxle

Ray: A Distributed Framework for Emerging AI Applications

https://github.com/Nico-Sch/RL-Chatbot

End-to-End Task-Completion Neural Dialogue Systems

https://github.com/NikolausBerl/Udacity_DRLN_Navigation_Project

Deep Reinforcement Learning with Double Q-learning

https://github.com/Nina-Konovalova/TSP-RL-Skoltech_project

Reinforcement Learning for Solving the Vehicle Routing Problem

https://github.com/NinaPi/Lunar_Causal_Network

Explainable Reinforcement Learning Through a Causal Lens

https://github.com/NitinVishalKulkarni/OfflineReinforcementLearning

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

https://github.com/NivNayman/XNAS

DARTS: Differentiable Architecture Search

https://github.com/Nkluge-correa/teeny-tiny_castle

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

https://github.com/NonameAuPlatal/Dual_Learning

Dual Learning for Machine Translation

https://github.com/NorthPolesky/GNNpaper

Deep Learning on Graphs: A Survey

https://github.com/OMS1996/Carla_The_RL_Self-Driving-Car

Deep Reinforcement Learning with Double Q-learning

https://github.com/OctThe16th/PPO-Keras

Proximal Policy Optimization Algorithms

https://github.com/Octavio-Pappalardo/MAML_for_RL_pytorch

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

https://github.com/Octavio-Pappalardo/RL2-implementation-pytorch

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

https://github.com/OctopusMind/RLHF_PPO

Proximal Policy Optimization Algorithms

https://github.com/Olloxan/Pytorch-A2C

Imagination-Augmented Agents for Deep Reinforcement Learning

https://github.com/Onysuke/chainer-grad-cam

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

https://github.com/OpenLLMAI/OpenLLaMA2

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

https://github.com/OptMLGroup/VRP-RL

Reinforcement Learning for Solving the Vehicle Routing Problem

https://github.com/OptimalPandemic/taurus

A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

https://github.com/OrthoDex/PCGrad-PyTorch

Gradient Surgery for Multi-Task Learning

https://github.com/Osrip/CriticalCoEvolution

Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents

https://github.com/Osrip/CriticalEvolution

Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents

https://github.com/Osrip/evolution_dynamical_regime

Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents

https://github.com/Ostyk/walk-bot

Proximal Policy Optimization Algorithms

https://github.com/PaddlePaddle/PaddleClas

GridMask Data Augmentation

https://github.com/PaddlePaddle/PaddleRec/tree/master/models/multitask/maml

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

https://github.com/PaddlePaddle/PaddleRec/tree/release/1.8.5/models/rerank/listwise

Sequential Evaluation and Generation Framework for Combinatorial Recommender System

https://github.com/PaddlePaddle/PaddleScience

Gradient Surgery for Multi-Task Learning

https://github.com/PanPalitta/phase_estimation

Learning in Quantum Control: High-Dimensional Global Optimization for Noisy Quantum Dynamics

https://github.com/Panda0406/Adversarial-Learning-Distant-Supervision-RE

Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning

https://github.com/Panda0406/Reinforcement-Learning-Distant-Supervision-RE

Robust Distant Supervision Relation Extraction via Deep Reinforcement Learning

https://github.com/Parapompadoo/Temporal_Action_Detection

A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning

https://github.com/PaulCharnay/Projet_AIF

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/Pechckin/MountainCar

Continuous control with deep reinforcement learning

https://github.com/PeteXC/Transfer-Learning

Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation

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