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dl_tutorials_4th's Introduction
- ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)
- Going Deeper with Convolutions (GoogLeNet)
- Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
- Deep Residual Learning for Image Recognition
- Residual Networks are Exponential Ensembles of Relatively Shallow Networks
- Wide Residual Networks
- Dropout- A Simple Way to Prevent Neural Networks from Overfitting
- Batch Normalization- Accelerating Deep Network Training by Reducing Internal Covariate Shift
Algorithms behind AlphaGo
- Mastering the game of Go with deep neural networks and tree search (AlphaGo)
- Momentum, NAG, AdaGrad, AdaDelta, RMSprop, AdaM
- ADAM: A Method For Stochastic Optimization
Restricted Boltzmann Machine
- A Practical Guide to Training Restricted Boltzmann Machines (RBM)
- Fully Convolutional Networks for Semantic Segmentation
- Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs
- Learning Deconvolution Network for Semantic Segmentation
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Weakly Supervised Localization
- Learning Deep Features for Discriminative Localization
- Is object localization for free? – Weakly-supervised learning with convolutional neural networks
- Rich feature hierarchies for accurate object detection and semantic segmentation
- Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
- Fast R-CNN
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- You Only Look Once: Unified, Real-Time Object Detection
- AttentionNet: Aggregating Weak Directions for Accurate Object Detection
- SSD: Single Shot MultiBox Detector
- Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction
- Multimodal Compact Bilinear Pooling for VQA
Deep reinforcement learning
- Playing Atari with Deep Reinforcement Learning
- Deep Reinforcement Learning with Double Q-learning
Recurrent Neural Networks
- Generating Sequences With Recurrent Neural Networks
- Distributed Representations of Words and Phrases and their Compositionality
- Show and Tell: A Neural Image Caption Generator
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- DenseCap: Fully Convolutional Localization Networks for Dense Captioning
- Texture Synthesis Using Convolutional Neural Networks
- Understanding Deep Image Representations by Inverting Them
- A Neural Algorithm of Artistic Style
Generative adversarial networks
- Generative Adversarial Networks
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
- Generative Adversarial Text to Image Synthesis
- Pixel Level Domain Transfer
- Basic Python usage (numpy, matplotlib, ..)
- Handling MNIST
- Logistic regression
- Multilayer Perceptron
- Convolutional Neural Network
- Denoising Autoencoders (+Convolutional)
- Class Activation Map
- Semantic Segmentation
- Using Custom Dataset
- Recurrent Neural Network
- Char-RNN
- Word2Vec
- Neural Style
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