Topic outline

  • Course schedule

    Lectures Exercise sessions
    		 Assignment deadlines Solution sessions
    Week 1
    01.03 Tue 14:15 1. Introduction
    03.03 Thu 14:15 2. Optimization
    04.03 Fri 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 01_mlp
     
    Week 2
    07.03 Mon 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 01_mlp
    08.03 Tue 14:15 3. Convolutional neural networks
    09.03 Wed 23:00 01_mlp
    11.03 Fri 10:15-11:45, 12:15-13:45 Exercises for assignment 02_cnn
     
    Week 3
    14.03 Mon 10:15-11:45, 12:15-13:45 Exercises for assignment 02_cnn
    15.03 Tue 10:15 01_mlp
    15.03 Tue 14:15 4. Regularization
    16.03 Wed 23:00 02_cnn
    18.03 Fri 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 03_reg
     
    Week 4
    21.03 Mon 10:15-11:45, 12:15-13:45 Exercises for assignment 03_reg
    22.03 Tue 10:15 02_cnn
    22.03 Tue 14:15 5. Recurrent neural networks
    23.03 Wed 23:00 03_reg
    25.03 Fri 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 04_rnn
     
    Week 5
    28.03 Mon 10:15-11:45, 12:15-13:45 Exercises for assignment 04_rnn
    29.03 Tue 10:15 03_reg
    29.03 Tue 14:15 6. Attention-based models
    30.03 Wed 23:00 04_rnn
    01.04 Fri 10:15-11:45, 12:15-13:45 Exercises for assignment 05_transformer
     
    Week 6
    04.04 Mon 10:15-11:45, 12:15-13:45 Exercises for assignment 05_transformer
    05.04 Tue 14:15 7. Graph neural networks
    05.04 Tue 10:15 04_rnn
    06.04 Wed 23:00 05_transformer
    08.04 Fri 10:15-11:45, 12:15-13:45 Exercises for assignment 06_gnn
     
    Week 7: Exam week
     
    Week 8
    19.04 Tue 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 06_gnn
    19.04 Tue 14:15 8. Autoencoders
    20.04 Wed 10:15
    		05_transformer
    20.04 Wed 23:00 06_gnn
    22.04 Fri 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 07_ae
     
    Week 9
    25.04 Mon 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 07_ae
    26.04 Tue 10:15 06_gnn
    26.04 Tue 14:15 9. Generative adversarial networks
    27.04 Wed 23:00 07_ae
    29.04 Fri 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 08_gan
     
    Week 10
    02.05 Mon 10:15-11:45, 12:15-13:45
    		 Exercises for assignment 08_gan
    03.05 Tue 10:15 07_ae
    03.05 Tue 14:15 10. Auto-regressive and flow-based models
    04.05 Wed 23:00 08_gan
     
    Week 11
    10.05 Tue 10:15 08_gan
    10.05 Tue 14:15 11. Deep learning with few labeled examples
    11.05 Wed 23:00 09_ar
     
    Week 12
    17.05 Tue 10:15 09_ar
    17.05 Tue 14:15 12. Unsupervised learning via denoising
    18.05 Wed 23:00 10_fewshot
    19.05 Thu 10:15 10_fewshot
     
    Week 13
    24.05 Tue 14:15 13. Guest lecture by Kyunghyun Cho (New York University)
     
    Week 14: Exam week

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