Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Deep Learning Tutorials for 10 Weeks
| Date | Stars |
|---|---|
| 2026-07-31 | 420 |
| 2026-08-03 | 420 |
| 2026-08-06 | 420 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Deep Learning Tutorial ### 45 Papers + TF implementations ## Topics (papers) ### Modern CNNs - Alex Krizhevsky, et al. "ImageNet Classification with Deep Convolutional Neural Networks", NIPS, 2012 - Christian Szegedy, et al. "Going Deeper with Convolutions", CVPR, 2015 - Christian Szegedy, et al. "Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning", ArXiv, 2016 - Kaiming He, et al. "Deep Residual Learning for Image Recognition", CVPR, 2016 - Andreas Veit, et al. "Residual Networks are Exponential Ensembles of Relatively Shallow Networks", ArXiv, 2016 - Sergey Zagoruyko and Nikos Komodakis "Wide Residual Networks", ArXiv, 2016 ### Regularization - Nitish Srivastava, et al. "Dropout- A Simple Way to Prevent Neural Networks from Overfitting", JMLR, 2014 - Sergey Ioffe and Christian Szegedy "Batch Normalization- Accelerating Deep Network Training by Reducing Internal Covariate Shift, ArXiv, 2015 ### Algorithms behind AlphaGo - David Silver et al. "Mastering the game of Go with deep neural networks and tree search", Nature, 2016 ### Optimization Methods - Momentum, NAG, AdaGrad, AdaDelta, RMSprop, ADAM - Diederik Kingma and Jimmy Bam "ADAM: A Method For Stochastic Optimization", ICLR, 2015 ### Restricted Boltzmann Machine - Geoffrey Hinton, "A Practical Guide to Training Restricted Boltzmann Machines", 2010 ### Semantic Segmentation - Jonathan Long et al. "Fully Convolutional Networks for Semantic Segmentation", CVPR, 2015 - Liang-Chieh Chen et al. "Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs", CVPR, 2015 - Hyeonwoo Noh et al. "Learning Deconvolution Network for Semantic Segmentation", ICCV, 2015 - Liang-Chieh Chen et al. "DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs", ArXiv, 2016 ### Weakly Supervised Localization - Maxime Oquab et al. "Is object localization for free? – Weakly-supervised learning with convolutional neural networks", CVPR, 2015 - Bolei Zhou et al. "Learning Deep Features for Discriminative Localization", CVPR, 2016 ### Image detection methods - Ross Girshick et al. "Rich feature hierarchies for accurate object detection and semantic segmentation", CVPR, 2014 - Kaiming He et al. "Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition", CVPR, 2015 - Ross Girshick, "Fast R-CNN", ICCV, 2015 - Shaoqing Ren et al. "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks", NIPS, 2015 - Joseph Redmon et al. "You Only Look Once: Unified, Real-Time Object Detection", CVPR, 2016 - Donggeun Yoo et al. "AttentionNet: Aggregating Weak Directions for Accurate Object Detection", ICCV, 2015 - Wei Liu et al. "SSD: Single Shot MultiBox Detector", ECCV, 2016 - Joseph Redmon, Ali Farhadi, "YOLO9000: Better, Faster, Stronger", ArXiv, 2017 ### Visual Q&A - Hyeonwoo Noh et al. "Image Question Answering using Convolutional Neural Network with Dynamic Parameter Prediction", CVPR, 2015 - Akira Fukui et al. "Multimodal Compact Bilinear Pooling for VQA", CVPR, 2016 ### Deep reinforcement learning - Volodymyr Mnih et al. "Playing Atari with Deep Reinforcement Learning", NIPS, 2013 - Hado van Hasselt et al. "Deep Reinforcement Learning with Double Q-learning", AAAI, 2016 ### Recurrent Neural Networks - Alex Graves, "Generating Sequences With Recurrent Neural Networks", ArXiv, 2013 ### Word embedding - Tomas Mikolov et al. "Distributed Representations of Words and Phrases and their Compositionality", NIPS, 2013 ### Image captioning - Oriol Vinyals et al. "Show and Tell: A Neural Image Caption Generator", CVPR, 2015 - Kelvin Xu et al. "Show, Attend and Tell: Neural Image Caption Generation with Visual Attention", ICML, 2015 - Justin Johnson et al. "DenseCap: Fully Convolutional Localization Networks for Dense Captioning", CVPR, 2016 ### Neural Styles - Leon A. Gatys et al. "Texture Synthesis Using Convolutional Neural Networks", NIPS, 2015 - Aravindh
Excerpt of 5,276 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:24bf8fa0be22cfb0, llm:topic: deep-learning-tutorial; description: Deep Learning Tutorials for 10 Weeks
matched fp:24bf8fa0be22cfb0, llm:topic: deep-learning-tutorial; description: Deep Learning Tutorials for 10 Weeks