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/fengye-lu/PyTorch-SRGAN

Searching for Activation Functions

https://github.com/ferrine/torch_anatgrad

Accelerating Natural Gradient with Higher-Order Invariance

https://github.com/feruxhi/thoughts

Continuous control with deep reinforcement learning

https://github.com/feryal/craft-env

Modular Multitask Reinforcement Learning with Policy Sketches

https://github.com/fgitmichael/SVAEfromSLAC

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

https://github.com/fgitmichael/TestModeDisentangling

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

https://github.com/fhbzc/FishAgentSimulation

Continuous control with deep reinforcement learning

https://github.com/fiberleif/evolution-strategies

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

https://github.com/fiberleif/nc_ddpg

Continuous control with deep reinforcement learning

https://github.com/fictivename/cesor_ppo

Efficient Risk-Averse Reinforcement Learning

https://github.com/fictivename/dcd_mujoco

Replay-Guided Adversarial Environment Design

https://github.com/fidler-lab/polyrnn-pp

Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++

https://github.com/fidler-lab/polyrnn-pp-pytorch

Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++

https://github.com/filipolszewski/prioritized-her

Energy-Based Hindsight Experience Prioritization

https://github.com/filippogiruzzi/deep_q_learning

Playing Atari with Deep Reinforcement Learning

https://github.com/filippogiruzzi/semantic_segmentation

CARLA: An Open Urban Driving Simulator

https://github.com/fiorenza2/OffCon3

Addressing Function Approximation Error in Actor-Critic Methods

https://github.com/fitushar/3D-Grad-CAM

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

https://github.com/flavioschneider/ml_papers_presentations

Continuous control with deep reinforcement learning

https://github.com/flexi-framework/tffb

Deep Reinforcement Learning for Turbulence Modeling in Large Eddy Simulations

https://github.com/floodsung/DDPG

Continuous control with deep reinforcement learning

https://github.com/floringogianu/atari-agents

Rainbow: Combining Improvements in Deep Reinforcement Learning

https://github.com/flow-project/ray

Ray: A Distributed Framework for Emerging AI Applications

https://github.com/flowersteam/explauto

Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning

https://github.com/flrngel/cpc-tensorflow

Representation Learning with Contrastive Predictive Coding

https://github.com/flymin/darts

DARTS: Differentiable Architecture Search

https://github.com/fmfn/BayesianOptimization

A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning

https://github.com/fmorenovr/Attention_Mechanism

Performing Deep Recurrent Double Q-Learning for Atari Games

https://github.com/fmu2/PyTorch-MAML

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

https://github.com/foersterrobert/AlphaZero

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

https://github.com/fomorians-oss/awr

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

https://github.com/foolyc/Meta-SGD

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

https://github.com/forevergj/multithreading_ppo_RND

Exploration by Random Network Distillation

https://github.com/forrestneo/FinRL-pytorch-tushare

Practical Deep Reinforcement Learning Approach for Stock Trading

https://github.com/francidellungo/Minigrid_HCI-project

Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations

https://github.com/frankhan91/DeepBSDE

Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations

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