{"id":15652018,"url":"https://github.com/rusty1s/deep-learning-on-graphs","last_synced_at":"2025-04-23T16:05:57.139Z","repository":{"id":94688510,"uuid":"69728849","full_name":"rusty1s/deep-learning-on-graphs","owner":"rusty1s","description":null,"archived":false,"fork":false,"pushed_at":"2017-11-27T06:17:41.000Z","size":38281,"stargazers_count":32,"open_issues_count":0,"forks_count":8,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-04-23T16:05:50.263Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"TeX","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rusty1s.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-10-01T08:56:34.000Z","updated_at":"2024-10-23T11:18:48.000Z","dependencies_parsed_at":"2023-03-14T01:30:55.791Z","dependency_job_id":null,"html_url":"https://github.com/rusty1s/deep-learning-on-graphs","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rusty1s%2Fdeep-learning-on-graphs","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rusty1s%2Fdeep-learning-on-graphs/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rusty1s%2Fdeep-learning-on-graphs/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rusty1s%2Fdeep-learning-on-graphs/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rusty1s","download_url":"https://codeload.github.com/rusty1s/deep-learning-on-graphs/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250468273,"owners_count":21435452,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-03T12:40:58.199Z","updated_at":"2025-04-23T16:05:57.109Z","avatar_url":"https://github.com/rusty1s.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Deep Learning\n\n## Resources\n\n* [Awesome Deep Vision](https://www.github.com/kjw0612/awesome-deep-vision)\n* [8 Inspirational Applications of Deep Learning](http://www.machinelearningmastery.com/inspirational-applications-deep-learning)\n* [Neural Networks and Deep Learning](http://www.neuralnetworksanddeeplearning.com) (Free Online Book)\n*  [A Guide to\n   Deep Learning](http://yerevann.com/a-guide-to-deep-learning/?utm_campaign=Revue%20newsletter\u0026utm_medium=Newsletter\u0026utm_source=revue)\n* [Deep Learning Weekly](http://www.deeplearningweekly.com) (Newsletter)\n* [TensorFlow](https://www.tensorflow.org) (Open Source Library)\n* [TensorFlow in a Nutshell](http://camron.xyz)\n* [A Year of Artificial Intelligence](https://ayearofai.com/)\n* [Introduction to Convolutional Neural\n  Networks](http://cs.nju.edu.cn/wujx/paper/CNN.pdf)\n\n## Python Tutorials\n\n* [Learn Python the hard way](https://learnpythonthehardway.org/book/)\n* [Style Guide](https://www.python.org/dev/peps/pep-0008/)\n* [Principle component analysis in python with\n  matplotlib](http://blog.nextgenetics.net/?e=42)\n\n## TensorFlow Tutorials\n\n* [Official](https://www.tensorflow.org/versions/r0.11/tutorials/index.html)\n* [Examples](https://github.com/aymericdamien/TensorFlow-Examples)\n\n## Paper\n\n* [A method for stochastic optimization](https://arxiv.org/pdf/1412.6980v8.pdf)\n  * Adam-Optimizer\n* [VGG 16/19](https://arxiv.org/pdf/1409.1556v6.pdf)\n  * [VGG in TensorFlow](https://www.cs.toronto.edu/~frossard/post/vgg16/)\n* Kontinuierliche Filter\n  * [Deep Function Machines: Generalized Neural Networks for Topological Layer\n    Expression](https://arxiv.org/pdf/1612.04799v1.pdf) (Section 4.1 und 4.2)\n* CNNs auf Daten mit variierenden Größen\n  * [Spatial Pyramid Pooling in Deep Convolutional Networks for Visual\n    Recognition](https://arxiv.org/pdf/1406.4729.pdf)\n  * [A convolutional neraul network for modelling\n    sentences](https://arxiv.org/pdf/1404.2188.pdf)\n* [Efficient and Scalable Computations with Sparse\n  Tensors](http://ieee-hpec.org/2012/index_htm_files/Baskaranpaper.pdf)\n\n## Reduce Overfitting\n\n* [Dropout: A Simple Way to Prevent Neural Networks from\n  Overfitting](https://www.cs.toronto.edu/~hinton/absps/JMLRdropout.pdf)\n* L2-Regularisierung\n* Batch-Normalisierung\n\n## Data\n\n* [CIFAR-10](http://www.cs.toronto.edu/%7Ekriz/cifar.html)\n  ([Citation](http://www.cs.toronto.edu/%7Ekriz/learning-features-2009-TR.pdf))\n  * [How to\n    use](https://www.tensorflow.org/versions/r0.12/tutorials/deep_cnn/index.html)\n* [ImageNet](http://image-net.org/)\n  * 224x224 klassische Größe für allgemeine Bildklassifikation\n  * [ILSVRC2014](http://image-net.org/challenges/LSVRC/2014/download-images-5jj5.php)\n  * [Random Ramblings on\n    ImageNet](http://peekaboo-vision.blogspot.de/2011/10/random-ramblings-on-imagenet.html)\n* [PascalVOC](http://host.robots.ox.ac.uk/pascal/VOC/)\n\n## Applications\n\n### Object Detection\n\n* Distance detection of objects\n* Detect friends on images based on their facebook profiles\n* Detect emotions from photos and represent them with an emoji\n* Detect rotations/poses of objects and replace them with objects that have a similar rotation\n\n### Vector Graphics\n\n* Convert svgs as graphs to input them in neural networks\n* Convert pixelbased images to vectorbased images\n* [Fake Chine Characters in Vector Format with TensorFlow](http://blog.otoro.net/2015/12/28/recurrent-net-dreams-up-fake-chinese-characters-in-vector-format-with-tensorflow/)\n* Create responsive svgs via Attention Detection (see [SVG has more potential](https://madebymike.com.au//writing/svg-has-more-potential/))\n* **Comparison:** Performance and accuracy tests on different networking tasks like classification on pixelbased images and pixelbased images converted to vector graphics\n\n### Fonts\n\n* Font Variant Generation\n* [Anaylizing 50k fonts using deep neural networks](https://erikbern.com/2016/01/21/analyzing-50k-fonts-using-deep-neural-networks/)\n\n### Image Generation\n\n* LowPoly Image Creation\n* [Create an Image from a Sketch](https://github.com/alexjc/neural-doodle)\n* [Image Analogies](https://github.com/awentzonline/image-analogies)\n* [Paint Photos in Style Of Any Artist](http://www.boredpanda.com/computer-deep-learning-algorithm-painting-masters/)\n* Create an image from a text (A pictures says more than thousand words)\n\n### Graph-based image classification\n\n* Efficiency and Performance by converting images to superpixels, segmentation graphs or svgs\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frusty1s%2Fdeep-learning-on-graphs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frusty1s%2Fdeep-learning-on-graphs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frusty1s%2Fdeep-learning-on-graphs/lists"}