SNU_DNNM

Mathematical Foundations of Deep Neural Networks, Fall 2022

[Week 1] Optimization and stochastic gradient descent
[Week 2] Shallow neural networks and logistic regression.
[Week 3] Multi-layer perceptron. Softmax regression.
[Week 4] Convolutional layers, pooling layers, GPU computing, LeNet
[Week 5] Data augmentation, regularization techniques: dropout, weight decay, early stopping
[Week 6] Weight initialization, VGGNet, backprop
[Week 7] Optimizers (ADAM, RMSProp), NiN network, GoogLeNet
[Week 8] Batch normalization, ResNet, DenseNet
[Week 9] ResNext, SENet, DNCNN, super-resolution, inverse problem
[Week 10-11] Flow models
[Week 12-13] Variational auto-encoders
[Week 14-15] Generative adversarial networks

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
README.md		README.md
hw10_6_.ipynb		hw10_6_.ipynb
hw10_Gamblers_ruin.ipynb		hw10_Gamblers_ruin.ipynb
hw10_derivative_trick.png		hw10_derivative_trick.png
hw10_flow_inpainting.ipynb		hw10_flow_inpainting.ipynb
hw10_plt1.png		hw10_plt1.png
hw10_plt2.png		hw10_plt2.png
hw10_plt3.png		hw10_plt3.png
hw11_flow_anomaly.ipynb		hw11_flow_anomaly.ipynb
hw12_minimax_logistic.ipynb		hw12_minimax_logistic.ipynb
hw12_swiss_roll_3.ipynb		hw12_swiss_roll_3.ipynb
hw12_swiss_roll_4.ipynb		hw12_swiss_roll_4.ipynb
hw12_swiss_roll_true.png		hw12_swiss_roll_true.png
hw1_conv1D.ipynb		hw1_conv1D.ipynb
hw1_wideMinima.ipynb		hw1_wideMinima.ipynb
hw2_LR_SGD.ipynb		hw2_LR_SGD.ipynb
hw2_SVM_SGD.ipynb		hw2_SVM_SGD.ipynb
hw2_phi_X_to_Y.ipynb		hw2_phi_X_to_Y.ipynb
hw2_twolayerSGD.ipynb		hw2_twolayerSGD.ipynb
hw3_threelayerSGD1.ipynb		hw3_threelayerSGD1.ipynb
hw3_threelayerSGD2.ipynb		hw3_threelayerSGD2.ipynb
hw4_Non_CE.ipynb		hw4_Non_CE.ipynb
hw4_lenet_original.ipynb		hw4_lenet_original.ipynb
hw5_label_memorization.ipynb		hw5_label_memorization.ipynb
hw5_mlp_backprop.ipynb		hw5_mlp_backprop.ipynb
hw6_ddescent.ipynb		hw6_ddescent.ipynb
hw7_LNiN.ipynb		hw7_LNiN.ipynb
hw7_bn_remove.ipynb		hw7_bn_remove.ipynb
hw9_anomaly_detection.ipynb		hw9_anomaly_detection.ipynb
hw9_loss.png		hw9_loss.png
hw9_normalizingFlow1d.ipynb		hw9_normalizingFlow1d.ipynb

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