Msdnet Gcn
ICLR 2018 reproducibility challenge - Multi-Scale Dense Convolutional Networks for Efficient Prediction
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Randomnas_release | 140 | 5 years ago | 4 | Python | ||||||
| Code release for paper "Random Search and Reproducibility for NAS" | ||||||||||
| Msdnet Gcn | 137 | 6 years ago | 3 | mit | Python | |||||
| ICLR 2018 reproducibility challenge - Multi-Scale Dense Convolutional Networks for Efficient Prediction | ||||||||||
| Moai | 47 |  | 2 | 3 months ago | 40 | October 05, 2022 | apache-2.0 | Python | ||
| moai is a PyTorch-based AI Model Development Kit (MDK) created to improve data-driven model workflows, design and reproducibility. | ||||||||||
| Reproducibilty Challenge Ecanet | 22 | 3 years ago | Python | |||||||
| Unofficial Implementation of ECANets (CVPR 2020) for the Reproducibility Challenge 2020. | ||||||||||
| Ner Lstm Cnn Pytorch | 18 | 6 years ago | 1 | Jupyter Notebook | ||||||
| End-to-end-Sequence-Labeling-via-Bi-directional-LSTM-CNNs-CRF-Tutorial | ||||||||||
| Cnn Incremental Learning | 14 | 6 years ago | Python | |||||||
| Reproducibility challenge project for a candidate paper of ICLR2018: Incremental Learning through Deep Adaption | ||||||||||
| Att_gconvs | 6 | 4 years ago | mit | Python | ||||||
| Code repository for the paper "Attentive Group Equivariant Convolutional Neural Networks" published at ICML 2020. | ||||||||||
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