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Sungjoon sjchoi86

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sjchoi86 / demo_06_gaussian_process.ipynb
Created October 5, 2020 14:13
GP example in Python
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sjchoi86 / demo_04_contrastive_loss.ipynb
Created October 2, 2020 03:14
Contrastive loss in SimCLR
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sjchoi86 / demo_PyBullet_01_SAC_AntBullet_Explained.ipynb
Created June 15, 2020 16:09
Self-contained SAC on PyBullet Ant
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sjchoi86 / demo_ML_02_VoronoiOptimisticOptimization.ipynb
Created May 26, 2020 06:29
VOO
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sjchoi86 / demo_ML_BayesianOptimization.ipynb
Created May 26, 2020 04:14
Bayesian Optimization with Expected Improvement Criterion
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sjchoi86 / demo_RAY_03_with_TensorFlow.ipynb
Created May 11, 2020 10:31
RAY with a TensorFlow Model
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sjchoi86 / demo_RAY_01_basic_usage.ipynb
Last active May 11, 2020 00:54
Simple implementation of a parameter server using RAY
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sjchoi86 / demo_save_restore_network.ipynb
Created April 29, 2020 22:52
A self-contained TF example of saving and restoring network variables.
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sjchoi86 / demo_ant_pybullet.py
Last active April 25, 2020 04:38
A minimalist example of using AntEnv with PyBullet
import time,gym
gym.logger.set_level(40)
import numpy as np
import pybullet as p
import pybullet_envs # env
p.connect(p.DIRECT)
env = gym.make("AntBulletEnv-v0")
_ = env.render(mode='human')
print ("action is from %s to %s"%
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sjchoi86 / demo_tf_rnn.ipynb
Created April 7, 2020 01:06
vibroptml/scripts/demo_tf_rnn.ipynb
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