Deep Generative Models
CS236
This course will not be offered AY22-23
Generative models are a key paradigm for probabilistic reasoning within graphical models and probabilistic programming languages. It is one of the exciting and rapidly-evolving fields of statistical machine learning and artificial intelligence. Recent advances in parameterizing generative models using deep neural networks, combined with progress in stochastic optimization methods, have enabled scalable modeling of complex, high-dimensional data including images, text, and speech. In this course, we will study the probabilistic foundations and learning algorithms for deep generative models and discuss application areas that have benefitted from deep generative models.
Topics Include
- Autoregressive models
- Variational autoencoders
- Normalizing flow models
- Generative adversarial networks
- Energy-based models
- Learning data distribution
- Application of various algorithms to decision making, finding analogies, and predicting future events
- Various applications to deep generative models including computer vision, speech and language processing
What You Need to Succeed
- A conferred bachelor’s degree with an undergraduate GPA of 3.0 or better
- Basic knowledge about machine learning from courses in artificial intelligence (CS221), probabilistic graphical models: principles and techniques (CS228), machine learning (CS229) or deep learning (CS230) or equivalents
- Students will work with computational and mathematical models and should have a basic knowledge of probabilities and calculus
- Proficiency in some programming language, preferably Python, required
What You Need To Get Started
Before enrolling in your first graduate course, you must complete an online application.
Don’t wait! While you can only enroll in courses during open enrollment periods, you can complete your online application at any time.
Once you have enrolled in a course, your application will be sent to the department for approval. You will receive an email notifying you of the department's decision after the enrollment period closes. You can also check your application status in your mystanfordconnection account at any time.
Learn more about the graduate application process.
