by Dima Kochkov
Generative Adversarial Networks
Presentation Summary
In this notebook, I present:
- Basic idea behind the GANs
- Cool applications
- Training code using TFGAN library
Examples
References
All Machine Learning
- by Will Wei · Deep Learning Partial Differential Equation (PDE)
- by Will Wei · Adaptive Boosting
- by Zeqian Li · Markov Decision Process and Reinforcement Learning
- by Yubo 'Paul' Yang · Kriging
- by Dima Kochkov · Generative Adversarial Networks
- by Xiongjie Yu · Neural Network on a Tensor Train
- by Will Wheeler · Reservoir Computing in the Time Domain
- by Yubo 'Paul' Yang · Gibbs Sampling
- by Matt Zhang · Predict Seizure with EEG
- by Matt Zhang · Adaptive Boosting (AdaBoost)
- by Benjamin Villalonga Correa · Introduction to Supervised Machine Learning
- by Dima Kochkov · Boltzmann Machines
Yubo "Paul" Yang ALGORITHM
machine learning