Difference between revisions of "Generative AI"
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* [http://en.wikipedia.org/wiki/Generative_model Generative model | Wikipedia] | * [http://en.wikipedia.org/wiki/Generative_model Generative model | Wikipedia] | ||
* [[Data Augmentation#Synthetic Labeling|Synthetic Labeling]] | * [[Data Augmentation#Synthetic Labeling|Synthetic Labeling]] | ||
| − | * Adversarial Networks | + | |
| − | ** [[Conditional Adversarial Architecture (CAA)]] | + | * Three main types: |
| − | ** [[Generative Adversarial Network (GAN)]] | + | ** [[Autoencoder (AE) / Encoder-Decoder]] |
| − | ** [[Semi-Supervised Learning with Generative Adversarial Network (SSL-GAN)]] | + | ** Sequence Models |
| − | ** [[Context-Conditional Generative Adversarial Network (CC-GAN)]] | + | *** [[Recurrent Neural Network (RNN)]] |
| + | *** [[Sequence to Sequence (Seq2Seq)]] | ||
| + | ** Adversarial Networks | ||
| + | *** [[Conditional Adversarial Architecture (CAA)]] | ||
| + | *** [[Generative Adversarial Network (GAN)]] | ||
| + | *** [[Semi-Supervised Learning with Generative Adversarial Network (SSL-GAN)]] | ||
| + | *** [[Context-Conditional Generative Adversarial Network (CC-GAN)]] | ||
Generative modeling asks how likely it is, given condition X, that you’ll observe outcome Y. The approach has proved incredibly potent and versatile. [https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/ How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine] | Generative modeling asks how likely it is, given condition X, that you’ll observe outcome Y. The approach has proved incredibly potent and versatile. [https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/ How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine] | ||
Revision as of 06:57, 2 October 2019
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- machines learn to perceive their surroundings by training only on data obtained by themselves
- AI Solver
- Generative Query Network (GQN)
- Discriminative vs. Generative
- Natural Language Generation (NLG)
- Generative model | Wikipedia
- Synthetic Labeling
- Three main types:
- Autoencoder (AE) / Encoder-Decoder
- Sequence Models
- Adversarial Networks
Generative modeling asks how likely it is, given condition X, that you’ll observe outcome Y. The approach has proved incredibly potent and versatile. How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine
Deep Generative Modeling
Agents
Generative Modeling Language
