Topic outline

  • Course schedule

    Lectures Exercise sessions
    		 Assignment deadlines Solution sessions
    Week 1
    28.02 Tue 14:15 1. Introduction
    02.03 Thu 14:15 2. Optimization (note a different lecture hall: A-sali (Aalto-sali) - Y202a)
    03.03 Fri 10:15-11:45
    		 In-person Q&A session for assignment 01_mlp
    03.03 Fri 12:15-13:45
    		 Online session for assignment 01_mlp
     
    Week 2
    06.03 Mon 10:15-11:45, 12:15-13:45
    		 Online sessions for assignment 01_mlp
    07.03 Tue 14:15 3. Convolutional neural networks
    08.03 Wed 23:00 01_mlp
    09.03 Thu 10:15 01_mlp
    10.03 Fri 10:15-11:45 In-person Q&A session for assignment 02_cnn
    10.03 Fri 12:15-13:45 Online session for assignment 02_cnn
     
    Week 3
    13.03 Mon 10:15-11:45, 12:15-13:45 Online sessions for assignment 02_cnn
    14.03 Tue 14:15 4. Regularization
    15.03 Wed 23:00 02_cnn
    16.03 Thu 10:15 02_cnn
    17.03 Fri 10:15-11:45
    		 In-person Q&A session for assignment 03_reg
    17.03 Fri 12:15-13:45
    		 Online session for assignment 03_reg
     
    Week 4
    20.03 Mon 10:15-11:45, 12:15-13:45 Online sessions for assignment 03_reg
    21.03 Tue 14:15 5. Recurrent neural networks
    22.03 Wed 23:00 03_reg
    23.03 Thu 10:15 03_reg
    24.03 Fri 10:15-11:45
    		 In-person Q&A session for assignment 04_rnn
    24.03 Fri 12:15-13:45
    		 Online session for assignment 04_rnn
     
    Week 5
    27.03 Mon 10:15-11:45, 12:15-13:45 Online sessions for assignment 04_rnn
    28.03 Tue 14:15 6. Attention-based models
    29.03 Wed 23:00 04_rnn
    30.03 Thu 10:15 04_rnn
    31.03 Fri 10:15-11:45 In-person Q&A session for assignment 05_transformer
    31.03 Fri 12:15-13:45 Online session for assignment 05_transformer
     
    Week 6
    03.04 Mon 10:15-11:45, 12:15-13:45 Online sessions for assignment 05_transformer
    04.04 Tue 14:15 7. Graph neural networks
    05.04 Wed 23:00 05_transformer
     
    06.04-12.04 Easter break
    Week 7
    13.04 Thu 10:15 05_transformer
    14.04 Fri 10:15-11:45 In-person Q&A session for assignment 06_gnn
    14.04 Fri 12:15-13:45 Online session for assignment 06_gnn
     
    Week 8: Exam week
     
    Week 9
    24.04 Mon 10:15-11:45, 12:15-13:45
    		 Online sessions for assignment 06_gnn
    25.04 Tue 14:15 8. Autoencoders
    26.04 Wed 23:00 06_gnn
    27.04 Thu 10:15 06_gnn
    28.04 Fri 10:15-11:45
    		 In-person Q&A session for assignment 07_ae
    28.04 Fri 12:15-13:45
    		 Online session for assignment 07_ae
     
    Week 9
    02.05 Tue 10:15-11:45, 12:15-13:45
    		 Online sessions for assignment 07_ae
    02.05 Tue 14:15 9. Unsupervised learning via denoising
    03.05 Wed 23:00 07_ae
    04.05 Thu 10:15 07_ae
    05.05 Fri 10:15-11:45
    		 In-person Q&A session for assignment 08_diffusion
    05.05 Fri 12:15-13:45
    		 Online session for assignment 08_diffusion
     
    Week 10
    08.05 Mon 10:15-11:45, 12:15-13:45
    		 Online sessions for assignment 08_diffusion
    09.05 Tue 14:15 10. Auto-regressive and flow-based models
    10.05 Wed 23:00 08_diffusion
    11.05 Thu 10:15 08_diffusion
     
    Week 11
    16.05 Tue 14:15 11. Generative adversarial networks
    17.05 Wed 23:00 09_ar
    19.05 Fri 10:15 09_ar
     
    Week 12
    23.05 Tue 14:15 11. Deep learning with few labeled examples
    24.05 Wed 23:00 10_gan
    25.05 Thu 10:15 10_gan
     
    Week 13
    30.05 Tue 14:15 12. Guest lecture: Miika Aittala (NVIDIA)
    31.05 Wed 23:00 11_fewshot
    01.06 Thu 10:15 11_fewshot
     
    Week 14: Exam week

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