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 13

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

9 years ago 13

A connection between generative adversarial networ...

9 years ago 14

RL²: Fast reinforcement learning via slow reinforc...

9 years ago 14

Variational lossy autoencoder

9 years ago 14

Extensions and limitations of the neural GPU

9 years ago 14

Semi-supervised knowledge transfer for deep learni...

9 years ago 15

Report from the self-organizing conference

9 years ago 16

Transfer from simulation to real world through lea...

9 years ago 15

Infrastructure for deep learning

9 years ago 15

Machine Learning Unconference

9 years ago 16

Special projects

9 years ago 15

Concrete AI safety problems

9 years ago 15

OpenAI technical goals

9 years ago 18

Generative models

9 years ago 15

Adversarial training methods for semi-supervised t...

9 years ago 18

OpenAI Gym Beta

9 years ago 16

Welcome, Pieter and Shivon!

9 years ago 16

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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