Stars
25
Forks
12
Language
None
Last Updated
Dec 26, 2020
Similar Repos
Repo | Language | Stars | Description | Updated At |
---|---|---|---|---|
Python | 2 | Chainer implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915). | Mar 25, 2019 | |
Lua | 126 | Torch implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915). | Sep 03, 2022 | |
Python | 261 | A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915) | Sep 19, 2022 | |
Python | 36 | Implementation of Deep Residual Learning / Residual Network for MSR paper http://arxiv.org/abs/1512.03385 | Mar 05, 2021 | |
Python | 21 | A tensorflow implementation of Wide Residual Networks(https://arxiv.org/abs/1605.07146) | Apr 12, 2022 | |
Python | 93 | A TensorFlow Implementation of Deep Spatio-Temporal Residual Networks (ST-ResNet): https://arxiv.org/abs/1610.00081 | Aug 31, 2022 | |
C++ | 25 | Caffe implementation of DOOBNet https://arxiv.org/abs/1806.03772 | Apr 07, 2022 | |
Cuda | 42 | caffe implementation of Group Normalization https://arxiv.org/abs/1803.08494 | Jul 21, 2022 | |
Python | 14 | Implementation of the paper https://arxiv.org/abs/1603.00448. | Oct 06, 2022 | |
Jupyter Notebook | 39 | implementation of paper https://arxiv.org/abs/2210.04559 | Apr 08, 2023 | |
MATLAB | 33 | PyTorch implementation for Deep Griffin-Lim Iteration paper(https://arxiv.org/abs/1903.03971) | Jul 12, 2022 | |
Python | 106 | Deep Residual Learning for Weakly-Supervised Relation Extraction: https://arxiv.org/abs/1707.08866 | Apr 30, 2022 | |
Python | 4 | Deep Residual Learning for Weakly-Supervised Relation Extraction: https://arxiv.org/abs/1707.08866 | May 28, 2018 | |
Python | 58 | Code for paper "Episodic Memory Deep Q-Networks" (https://arxiv.org/abs/1805.07603), IJCAI 2018 | Sep 10, 2022 | |
Python | 9 | Official Implementation of paper https://arxiv.org/abs/1801.02612 | Sep 21, 2022 | |
Jupyter Notebook | 22 | Official implementation of https://arxiv.org/abs/2105.08655 paper | Sep 23, 2022 | |
Jupyter Notebook | 11 | Official implementation of https://arxiv.org/abs/2108.11554 paper | May 08, 2022 | |
Python | 99 | A TensorFlow implementation of Relational Graph Attention Networks, paper: https://arxiv.org/abs/1904.05811 | Sep 26, 2022 | |
Python | 149 | The implementation of paper https://arxiv.org/abs/1704.07556, ACL 2017 | May 23, 2022 | |
Python | 2 | Official PyTorch Implementation for the paper https://arxiv.org/abs/2302.13929. | May 10, 2023 | |
Jupyter Notebook | 42 | A Caffe implementation of http://arxiv.org/abs/1512.07928 | Jun 29, 2022 | |
Python | 53 | Paper: https://arxiv.org/abs/1702.02285 | Aug 29, 2022 | |
Jupyter Notebook | 21 | paper: https://arxiv.org/abs/2110.08037 | Apr 22, 2023 | |
Python | 155 | Source code for the paper "Hyperbolic Neural Networks", https://arxiv.org/abs/1805.09112 | Oct 17, 2022 | |
Python | 22 | Implement the paper: https://arxiv.org/abs/1907.05321 | Sep 27, 2022 | |
Jupyter Notebook | 56 | implement the paper" Very Deep Convolutional Networks for Natural Language Processing"(https://arxiv.org/abs/1606.01781 ) in tensorflow | Apr 17, 2022 | |
Python | 76 | Deep Residual Learning for Image Recognition, http://arxiv.org/abs/1512.03385 | Jul 25, 2022 | |
Lua | 21 | Torch implementation of the paper "ShakeDrop regularization" (https://arxiv.org/abs/1802.02375). | Jun 09, 2021 | |
Python | 4 | Chainer implementation of the paper "Xception: Deep Learning with Depthwise Separable Convolutions" (https://arxiv.org/abs/1610.02357). | Feb 13, 2020 | |
Python | 57 | Maxout Networks TensorFlow implementation presented in https://arxiv.org/abs/1302.4389 | Aug 31, 2022 | |
Python | 7 | Paper link: https://arxiv.org/abs/2001.01431 | Aug 11, 2022 | |
Python | 203 | Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf) | Oct 06, 2022 | |
Jupyter Notebook | 3 | Implementation of the paper titled - U-Net: Convolutional Networks for Biomedical Image Segmentation @ https://arxiv.org/abs/1505.04597 | Aug 22, 2022 | |
Python | 50 | PyTorch implementation of Unsupervised Deep Homography: https://arxiv.org/abs/1709.03966 | Jun 12, 2022 | |
Jupyter Notebook | 50 | Code for the paper https://arxiv.org/abs/2003.00827 | Aug 30, 2022 | |
Python | 54 | The repository for paper https://arxiv.org/abs/1902.10840 | Mar 31, 2022 | |
Python | 2 | Chainer implementation of the paper "Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning" … | Dec 06, 2019 | |
Jupyter Notebook | 2 | PyTorch implementation of the paper "AutomaticStructured Variational Inference" (https://arxiv.org/abs/2002.00643) | May 20, 2022 | |
Python | 2537 | Graph Attention Networks (https://arxiv.org/abs/1710.10903) | Oct 17, 2022 | |
Python | 81 | Hybrid Code Networks https://arxiv.org/abs/1702.03274 | Feb 08, 2022 | |
Python | 139 | Keras implementation for "Deep Networks with Stochastic Depth" http://arxiv.org/abs/1603.09382 | Oct 13, 2022 | |
Python | 4 | PyTorch implementation of DeepCaps : Going Deeper with Capsule Networks. Original research paper : https://arxiv.org/abs/1904.09546. | May 15, 2023 | |
Python | 108 | pytorch implementation of Independently Recurrent Neural Networks https://arxiv.org/abs/1803.04831 | Aug 07, 2022 | |
None | 58 | The tensorflow implementation of NIPS2016 paper "LightRNN: Memory and Computation-Efficient Recurrent Neural Networks" (https://arxiv.org/abs/1610.09893) | Jul 05, 2021 | |
Python | 2 | The tensorflow implementation of NIPS2016 paper "LightRNN: Memory and Computation-Efficient Recurrent Neural Networks" (https://arxiv.org/abs/1610.09893) | Jan 10, 2018 | |
Cuda | 6080 | Code and data for paper "Deep Painterly Harmonization": https://arxiv.org/abs/1804.03189 | Oct 16, 2022 | |
Python | 475 | Deep Graph Infomax (https://arxiv.org/abs/1809.10341) | Oct 17, 2022 | |
Python | 27 | Remplementation of paper https://arxiv.org/abs/1705.08665 | Oct 02, 2022 | |
Python | 22 | Code for paper https://arxiv.org/abs/2102.13186 | Sep 23, 2022 | |
Python | 149 | Pytorch implementation for paper of "A DEEP REINFORCED MODEL FOR ABSTRACTIVE SUMMARIZATION". https://arxiv.org/abs/1705.04304 | Jul 31, 2022 |