Archive - DiekNews

OpenAI and Microsoft

On the quantitative analysis of decoder-based generative models

A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models

RL²: Fast reinforcement learning via slow reinforcement learning

Variational lossy autoencoder

Extensions and limitations of the neural GPU

Semi-supervised knowledge transfer for deep learning from private training data

Report from the self-organizing conference

Transfer from simulation to real world through learning deep inverse dynamics model

Infrastructure for deep learning

Latest

OpenAI and Microsoft

9 years ago 31

On the quantitative analysis of decoder-based gene...

9 years ago 31

A connection between generative adversarial networ...

9 years ago 33

RL²: Fast reinforcement learning via slow reinforc...

9 years ago 32

Variational lossy autoencoder

9 years ago 33

Extensions and limitations of the neural GPU

9 years ago 33

Semi-supervised knowledge transfer for deep learni...

9 years ago 37

Report from the self-organizing conference

9 years ago 43

Transfer from simulation to real world through lea...

9 years ago 42

Infrastructure for deep learning

9 years ago 41

Machine Learning Unconference

9 years ago 48

Special projects

9 years ago 42

Concrete AI safety problems

1 decade ago 42

OpenAI technical goals

1 decade ago 44

Generative models

1 decade ago 42

Adversarial training methods for semi-supervised t...

1 decade ago 44

OpenAI Gym Beta

1 decade ago 43

Welcome, Pieter and Shivon!

1 decade ago 42

OpenAI and Microsoft

On the quantitative analysis of decoder-based generative models

A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models

RL²: Fast reinforcement learning via slow reinforcement learning

Variational lossy autoencoder

Extensions and limitations of the neural GPU

Semi-supervised knowledge transfer for deep learning from private training data

Report from the self-organizing conference

Transfer from simulation to real world through learning deep inverse dynamics model

Infrastructure for deep learning

Latest

OpenAI and Microsoft

On the quantitative analysis of decoder-based gene...

A connection between generative adversarial networ...

RL²: Fast reinforcement learning via slow reinforc...

Variational lossy autoencoder

Extensions and limitations of the neural GPU

Semi-supervised knowledge transfer for deep learni...

Report from the self-organizing conference

Transfer from simulation to real world through lea...

Infrastructure for deep learning

Machine Learning Unconference

Special projects

Concrete AI safety problems

OpenAI technical goals

Generative models

Adversarial training methods for semi-supervised t...

OpenAI Gym Beta

Welcome, Pieter and Shivon!

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