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Reinforcement Learning

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코드

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

https://github.com/tarolangner/mri-biometry

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

https://github.com/tatp22/multidim-positional-encoding

Translating Math Formula Images to LaTeX Sequences Using Deep Neural Networks with Sequence-level Training

https://github.com/tatsu-lab/linguistic_calibration

Proximal Policy Optimization Algorithms

https://github.com/tccnchsu/study

A Survey of Deep Network Solutions for Learning Control in Robotics: From Reinforcement to Imitation

https://github.com/tcmxx/CNTKUnityTools

Playing Atari with Deep Reinforcement Learning

https://github.com/teddykoker/image-forensics

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

https://github.com/tegg89/DLCamp_Jeju2018

Continuous control with deep reinforcement learning

https://github.com/tegg89/magnn

Continuous control with deep reinforcement learning

https://github.com/tegg89/mann

Continuous control with deep reinforcement learning

https://github.com/tegg89/paper-notes

World Models

https://github.com/tencent-ailab/Arena

Arena: a toolkit for Multi-Agent Reinforcement Learning

https://github.com/tennisonliu/bayesian-neural-network

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

https://github.com/tensorflow/deepmath/tree/master/deepmath/deephol

HOList: An Environment for Machine Learning of Higher-Order Theorem Proving

https://github.com/tensorflow/minigo

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

https://github.com/tensorflow/models/tree/archive/research/deep_contextual_bandits

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

https://github.com/tensorflow/models/tree/archive/research/tcn

Time-Contrastive Networks: Self-Supervised Learning from Video

https://github.com/tensorflow/models/tree/master/research/deep_contextual_bandits

Weight Uncertainty in Neural Networks

https://github.com/tensorflow/models/tree/master/research/deeplab

Progressive Neural Architecture Search

https://github.com/tensorflow/models/tree/master/research/efficient-hrl

Data-Efficient Hierarchical Reinforcement Learning

https://github.com/tensorflow/models/tree/master/research/slim

Progressive Neural Architecture Search

https://github.com/tensorflow/models/tree/master/research/tcn

Time-Contrastive Networks: Self-Supervised Learning from Video

https://github.com/tensorflow/tpu/tree/master/models/official/amoeba_net

Regularized Evolution for Image Classifier Architecture Search

https://github.com/tensorforce/tensorforce

LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations

https://github.com/tensorpack/tensorpack/tree/master/examples/A3C-Gym

Asynchronous Methods for Deep Reinforcement Learning

https://github.com/tensorpack/tensorpack/tree/master/examples/DeepQNetwork

Playing Atari with Deep Reinforcement Learning

https://github.com/tenvinc/CS4246-Project

Deep Q-learning from Demonstrations

https://github.com/teo-sl/DPLAN_pytorch

Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data

https://github.com/terne/dtuproject

Deep Reinforcement Learning for Programming Language Correction

https://github.com/tesatory/hsp

Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning

https://github.com/teticio/llama-squad

LIMA: Less Is More for Alignment

https://github.com/tfolkman/deep-learning-experiments

Deep Reinforcement Learning for Dialogue Generation

https://github.com/thaihungle/SHM

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning

https://github.com/thainv0212/re-ddpg

Continuous control with deep reinforcement learning

https://github.com/theSparta/neural-symbolic-machines

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

https://github.com/theSparta/off_policy_mujoco

Off-Policy Deep Reinforcement Learning without Exploration

https://github.com/theamrzaki/text_summurization_abstractive_methods

A Deep Reinforced Model for Abstractive Summarization

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