cb614611757
Institute of Automation, Chinese Academy of Sciences Reinforcement learning
haidian district, Beijing China
Pinned Repositories
Articles
:notebook_with_decorative_cover: 简书文章中的材料
asymmetric-actor-critic
Implementation of Asymmetric Actor Critic for Image-Based Robot Learning in Tensorflow.
Attention-ATN
Attack-IJCAI-2019-AAAC:An Attention-ATN to generate Adversarial Examples
deep-rl
Collection of Deep Reinforcement Learning algorithms
Kuka_Pybullet-for-pick-and-place
# Kuka_Pybullet for pick and place This script can be used for the research of robotic reinforcement learning. The script builds a simulation environment for robot manipulation about pick and place based on the pybullet simulation environment. Users can incorporate this environment into the reinforcement learning algorithm for online data collection and performance evaluation. ## Instructions The code was tested on Linux with Python3.6. Use of virtualenvs is recommended. To run: ``` pip install -r requirements.txt python main.py
MLDG
The demo codes for the MLDG paper "Learning to Generalize: Meta-Learning for Domain Generalization", https://arxiv.org/abs/1710.03463, https://arxiv.org/pdf/1710.03463.pdf
models
Models and examples built with TensorFlow
nips-2017-adversarial
Adversarial Attacks and Defenses of Image Classifiers, NIPS 2017 competition track
pytorch-maml
PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400
pytorch-maml-rl
Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch
cb614611757's Repositories
cb614611757/Kuka_Pybullet-for-pick-and-place
# Kuka_Pybullet for pick and place This script can be used for the research of robotic reinforcement learning. The script builds a simulation environment for robot manipulation about pick and place based on the pybullet simulation environment. Users can incorporate this environment into the reinforcement learning algorithm for online data collection and performance evaluation. ## Instructions The code was tested on Linux with Python3.6. Use of virtualenvs is recommended. To run: ``` pip install -r requirements.txt python main.py
cb614611757/Attention-ATN
Attack-IJCAI-2019-AAAC:An Attention-ATN to generate Adversarial Examples
cb614611757/asymmetric-actor-critic
Implementation of Asymmetric Actor Critic for Image-Based Robot Learning in Tensorflow.
cb614611757/deep-rl
Collection of Deep Reinforcement Learning algorithms
cb614611757/nips-2017-adversarial
Adversarial Attacks and Defenses of Image Classifiers, NIPS 2017 competition track
cb614611757/Articles
:notebook_with_decorative_cover: 简书文章中的材料
cb614611757/MLDG
The demo codes for the MLDG paper "Learning to Generalize: Meta-Learning for Domain Generalization", https://arxiv.org/abs/1710.03463, https://arxiv.org/pdf/1710.03463.pdf
cb614611757/models
Models and examples built with TensorFlow
cb614611757/pytorch-maml
PyTorch implementation of MAML: https://arxiv.org/abs/1703.03400
cb614611757/pytorch-maml-rl
Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch
cb614611757/Rainbow_ddpg
cb614611757/rl_paper
paper which about reinforcement learning in Dec 2018
cb614611757/tensorflow-allreduce