Sung Yub Kim presentations

Aktivität
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Data Mining with R CH1 요약

Vor 8 Jahren • 1339 Aufrufe

Linear models for classification

Vor 7 Jahren • 2571 Aufrufe

Statistics for deep learning

Vor 7 Jahren • 266 Aufrufe

Machine learning for deep learning

Vor 7 Jahren • 320 Aufrufe

Probability distributions for ml

Vor 7 Jahren • 462 Aufrufe

MM framework for RL

Vor 6 Jahren • 1042 Aufrufe

Connection between Bellman equation and Markov Decision Processes

Sungjoon Choi • Vor 7 Jahren

[한국어] Safe Multi-Agent Reinforcement Learning for Autonomous Driving

Kiho Suh • Vor 6 Jahren

Backpropagation in Convolutional Neural Network

Hiroshi Kuwajima • Vor 10 Jahren

Deep generative model.pdf

Hyungjoo Cho • Vor 6 Jahren

Attention mechanisms with tensorflow

Keon Kim • Vor 7 Jahren

Normalization 방법

홍배 김 • Vor 7 Jahren

Kernel, RKHS, and Gaussian Processes

Sungjoon Choi • Vor 7 Jahren

Understanding deep learning requires rethinking generalization (2017) 1/2

정훈 서 • Vor 7 Jahren

Understanding deep learning requires rethinking generalization (2017) 2 2(2)

정훈 서 • Vor 7 Jahren

Visualizing data using t-SNE

홍배 김 • Vor 7 Jahren

Generative adversarial networks

남주 김 • Vor 7 Jahren

Layer Normalization@NIPS+読み会・関西

Keigo Nishida • Vor 7 Jahren

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

홍배 김 • Vor 7 Jahren

2017 tensor flow dev summit

Tae Young Lee • Vor 7 Jahren

Continuous control with deep reinforcement learning (DDPG)

Taehoon Kim • Vor 7 Jahren

텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016

Taehoon Kim • Vor 7 Jahren

지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016

Taehoon Kim • Vor 7 Jahren

Meta-Learning with Memory Augmented Neural Networks

홍배 김 • Vor 7 Jahren

Generalization of Tensor Factorization and Applications

Kohei Hayashi • Vor 11 Jahren

머피의 머신러닝 : Gaussian Processes

Jungkyu Lee • Vor 10 Jahren

machine learning deep learning reinforcemen learning

Sung Yub Kim

Präsentationen

Data Mining with R CH1 요약

Linear models for classification

Statistics for deep learning

Machine learning for deep learning

Probability distributions for ml

MM framework for RL

Gefällt mir

Connection between Bellman equation and Markov Decision Processes

[한국어] Safe Multi-Agent Reinforcement Learning for Autonomous Driving

Backpropagation in Convolutional Neural Network

Deep generative model.pdf

Attention mechanisms with tensorflow

Normalization 방법

Kernel, RKHS, and Gaussian Processes

Understanding deep learning requires rethinking generalization (2017) 1/2

Understanding deep learning requires rethinking generalization (2017) 2 2(2)

Visualizing data using t-SNE

Generative adversarial networks

Layer Normalization@NIPS+読み会・関西

InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets

2017 tensor flow dev summit

Continuous control with deep reinforcement learning (DDPG)

텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016

지적 대화를 위한 깊고 넓은 딥러닝 PyCon APAC 2016

Meta-Learning with Memory Augmented Neural Networks

Generalization of Tensor Factorization and Applications

머피의 머신러닝 : Gaussian Processes