| Date | Lecture | Teacher | Materials | Notes / Reading |
|---|---|---|---|---|
| 17.02.2021 | 1. Introduction to Neural Networks | BF | slides record | McCulloch-Pitts Neuron |
| 24.02.2021 | 2. The Power of Neural Networks | BF | slides record | |
| 03.03.2021 | 3. Backpropagation | AS | slides record | |
| 10.03.2021 | 4. Stochastic Gradient Descent (SGD) | AS | slides record | |
| 17.03.2021 | 5. Convolutional Neural Networks | AS | slides record | A guide to convolution arithmetic for deep learning |
| 24.03.2021 | 6. Data Augmentation, Weight Initialization, Batch Normalization | BF | slides record | |
| 31.03.2021 | 7. Regularization Methods for NNs | AS | slides record | |
| 07.04.2021 | 8. Adaptive SGD Methods | AS | slides record | |
| 14.04.2021 | 9. Adversarial Patterns. Robust Learning Approaches | BF | slides record | |
| 21.04.2021 | 10. Learning Representations, Stochastic EM | AS | slides record | |
| 28.04.2021 | 11. Variational Autoencoders | BF | slides record | VAE tutorial |
| 05.05.2021 | 12. Guest lecture: Deep Metric Learning | Giorgos Tolias | slides record | |
| 12.05.2021 | — Rector's day — | |||
| 19.05.2021 | 13. Recurrent Neural Networks. Recurrent Back-Propagation | BF | slides |