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#Generative_Adversarial_Networks (GANs) CS236G Course | Sharon Zhou
| Stanford University
- Learn and build generative adversarial networks (GANs), from their simplest form to state-of-the-art models.
- Implement, debug, and train GANs as part of a novel and substantial course project.
- Gaining familiarity with the latest cutting-edge literature on GANs.
- Reward risk-taking and creative exploration.
https://cs236g.stanford.edu/
#Course #GAN #Stanford
@ml_nlp_cv
| Stanford University
- Learn and build generative adversarial networks (GANs), from their simplest form to state-of-the-art models.
- Implement, debug, and train GANs as part of a novel and substantial course project.
- Gaining familiarity with the latest cutting-edge literature on GANs.
- Reward risk-taking and creative exploration.
https://cs236g.stanford.edu/
#Course #GAN #Stanford
@ml_nlp_cv
Deep Generative Modelling:
A Comparative Review of #VAEs, #GANs, Normalizing Flows, Energy-Based and Autoregressive Models
https://arxiv.org/abs/2103.04922
#Generative_Models #Variational_Autoencoders #Generative_Adversarial_Networks #Autoregressive_Models #Review_Paper
@ml_nlp_cv
A Comparative Review of #VAEs, #GANs, Normalizing Flows, Energy-Based and Autoregressive Models
https://arxiv.org/abs/2103.04922
#Generative_Models #Variational_Autoencoders #Generative_Adversarial_Networks #Autoregressive_Models #Review_Paper
@ml_nlp_cv