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awesome-deep-reinforcement-learning

Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...
https://github.com/jgvictores/awesome-deep-reinforcement-learning

Last synced: about 2 hours ago
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  • Neural Networks (NN) and Deep Neural Networks (DNN)

    • NN/DNN Datasets

    • NN/DNN Pretrained Models

      • keras web - team/keras/tree/master/keras/applications), [keras 2](https://github.com/keras-team/keras-applications), [pytorch](https://pytorch.org/docs/stable/torchvision/models.html), [caffe](https://github.com/BVLC/caffe/wiki/Model-Zoo), [ONNX](https://github.com/onnx/models) (pytorch/caffe2).
      • keras
      • keras by keras - team/keras/tree/e15533e6c725dca8c37a861aacb13ef149789433/keras/applications)) / [keras by kaggle](https://www.kaggle.com/keras) / [pytorch by kaggle](https://www.kaggle.com/pytorch)
      • keras
      • keras
      • caffe by original VGG author
      • gensim
    • NN/DNN Techniques Misc

    • NN/DNN Visualization and Explanation

      • keras - deep-learning-neural-network-model-keras/), [2](https://github.com/keplr-io/quiver), [3](https://raghakot.github.io/keras-vis/), [4](https://www.kaggle.com/amarjeet007/visualize-cnn-with-keras)
      • tensorboard
    • NN/DNN Software Frameworks

    • NN/DNN Models

      • 1
      • arxiv - fcis).
      • arxiv - freiburg.de/people/ronneber/u-net/).
      • arxiv
      • arxiv - Single-Shot-MultiBox-Detector)
      • arxiv
      • arxiv - brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn-34ea83205de4)): Fast R-CNN, Faster R-CNN, Mask R-CNN.
      • 1 - tricks.com/cnn/understand-resnet-alexnet-vgg-inception/), [3](https://medium.com/@sidereal/cnns-architectures-lenet-alexnet-vgg-googlenet-resnet-and-more-666091488df5)
      • arxiv
      • arxiv
      • arxiv
      • arxiv
      • arxiv - 3 weeks.
      • arxiv - 7 million parameters, via smaller convs. A more aggressive cropping approach than that of Krizhevsky. Batch normalization, image distortions, RMSprop. Uses 9 novel "Inception modules" (at each layer of a traditional ConvNet, you have to make a choice of whether to have a pooling operation or a conv operation as well as the choice of filter size; an Inception module performa all these operations in parallel), and no fully connected. Trained on CPU (estimated as weeks via GPU) implemented in DistBelief (closed-source predecessor of TensorFlow). Variants ([summary](https://towardsdatascience.com/a-simple-guide-to-the-versions-of-the-inception-network-7fc52b863202)): v1, v2, v4, resnet v1, resnet v2; v9 ([slides](http://lsun.cs.princeton.edu/slides/Christian.pdf)). Also see [Xception (2017)](https://arxiv.org/pdf/1610.02357.pdf) paper.
      • arxiv
      • doi - justified finer tuning and visualization (namely Deconvolutional Network).
      • doi
      • Geometric deep learning
      • ref
      • tensorflow
      • arxiv - painterly-harmonization)
      • arxiv - photo-styletransfer)
      • arxiv - style), keras [1](https://github.com/keras-team/keras/blob/master/examples/neural_style_transfer.py) [2](https://github.com/titu1994/Neural-Style-Transfer) [3](https://github.com/handong1587/handong1587.github.io/blob/master/_posts/deep_learning/2015-10-09-fun-with-deep-learning.md) [4](https://medium.com/mlreview/making-ai-art-with-style-transfer-using-keras-8bb5fa44b216)
      • arxiv - pytorch)
      • arxiv
      • arxiv - Adversarial-Networks)
      • arxiv
      • arxiv
      • FTTNet - Time Speaker-Dependent Neural Vocoder". [pytorch](https://github.com/mozilla/FFTNet)
      • keras
      • keras - image-similarity)
      • arxiv
      • wikipedia
      • 1
      • ref
      • 1
      • 1
      • facebookresearch/Detectron
      • thunlp/GNNPapers
      • chihming/awesome-network-embedding
      • DLG
      • pytorch
      • tensorflow/gnn
      • pytorch
      • ref
      • caffe
      • hindupuravinash/the-gan-zoo
      • CycleGAN - Yan Zhu et Al; Berkeley; "Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks". [torch](https://github.com/junyanz/CycleGAN) and migrated to [pytorch](https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix).
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      • doi
      • ref
      • 1
      • ref
      • 1
      • facebookresearch/Detectron
      • 1
      • 1
      • 1
      • ref
      • 1
      • 1
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      • 1
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      • 1
      • doi - 61 million parameters, split into 2 pipelines to enable 5-6 day GTX 580 GPU training (while CPU data augmentation).
      • 1
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      • ref
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  • Reinforcement Learning (RL) and Deep Reinforcement Learning (DRL)

    • RL/DRL Algorithms

    • RL/DRL Algorithm Implementations and Software Frameworks

      • RL-Glue - glue-ext/wikis/RLGlueCore.wiki)) (API: C/C++, Java, Matlab, Python, Lisp) (support: Alberta)
  • Similar pages

  • General Machine Learning (ML)