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Deep learning tutorials (third edition)
License: MIT License
dl_tutorials_3rd's Introduction
Deep learning tutorials (third eddition)
Introduction to deep learning and tools
- ImageNet Classification with Deep Convolutional Neural Networks (AlexNet)
- Going Deeper with Convolutions (GoogleLenet)
Monte-Carlo Tree Search with CNN
- Mastering the game of Go with deep neural networks and tree search (AlphaGo)
- Dropout- A Simple Way to Prevent Neural Networks from Overfitting
- Batch Normalization- Accelerating Deep Network Training by Reducing Internal Covariate Shift
Optimization methods - Momentum, NAG, AdaGrad, AdaDelta, RMSprop, AdaM
- ADAM: A Method For Stochastic Optimization
- A Practical Guide to Training Restricted Boltzmann Machines (RBM)
Semantic segmentation methods
- 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 methods
- 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
Introduction to RNN and LSTM
- Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction
- Multimodal Compact Bilinear Pooling for VQA
- Accurate Image Super-Resolution Using Very Deep Convolutional Networks
- Deeply-Recursive Convolutional Network for Image Super-Resolution
Deep reinforcement learning
- Playing Atari with Deep Reinforcement Learning
- Deep Reinforcement Learning with Double Q-learning
- 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
Residual network and analyses
- Deep Residual Learning for Image Recognition
- Residual Networks are Exponential Ensembles of Relatively Shallow Networks
- Wide Residual Networks
- Texture Synthesis Using Convolutional Neural Networks
- Understanding Deep Image Representations by Inverting Them
- A Neural Algorithm of Artistic Style
- Practical Bayesian Optimization of Machine Learning Algorithms
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
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