CS-E4070 - Special Course in Machine Learning and Data Science: Advanced Topics in Deep Learning, 18.04.2019-23.05.2019
This course space end date is set to 23.05.2019 Search Courses: CS-E4070
Topic outline
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During the course, we will discuss advanced deep learning models. Each student will present one topic and implement the presented model in PyTorch. The topics of the seminars will be selected according to the students' interests. The list of possible topics (note that we will not cover deep reinforcement learning in the course):
1. Optimization and regularization- Adversarial deep learning, adversarial training
- Bayesian neural networks (reserved)
- Capsule networks (reserved)
- Learning image metrics
- Attention is all you need, universal transformers (reserved)
- Neural Turing machine (reserved)
- Deep autoregressive models (reserved)
- Variational auto-encoders (reserved)
- Advances in GANs (reserved)
- BERT (reserved)
- Semi-supervised learning: mean teacher (reserved)
- Semi-supervised learning: virtual adversarial training (reserved)
- Few-shot learning: Prototypical networks, MAML
- Conditional neural processes
- Graph convolution networks (reserved)
- Interaction networks
Registration is closed.
- Adversarial deep learning, adversarial training