Semantic_role_labeling_deep_learning
SRL deep learning model is based on DB-LSTM which is described in this paper : [End-to-end learning of semantic role labeling using recurrent neural networks](http://www.aclweb.org/anthology/P15-1109
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| How To Learn Deep Learning | 644 | a year ago | mit | |||||||
| A top-down, practical guide to learn AI, Deep learning and Machine Learning. | ||||||||||
| Dissect | 202 | 3 years ago | 3 | other | Python | |||||
| Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network" | ||||||||||
| Semantic_role_labeling_deep_learning | 18 | 7 years ago | 1 | mit | Python | |||||
| SRL deep learning model is based on DB-LSTM which is described in this paper : [End-to-end learning of semantic role labeling using recurrent neural networks](http://www.aclweb.org/anthology/P15-1109) | ||||||||||
| Semantic Role Labeling | 15 | 6 years ago | Python | |||||||
| Deep semantic role labeling using Tensorflow | ||||||||||
| Chainer Meanteachers | 11 | 6 years ago | Python | |||||||
| Chainer implementation of the paper "Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results" (https://arxiv.org/abs/1703.01780) | ||||||||||
| Time Slu | 9 | 7 years ago | Python | |||||||
| Dynamic Time-Aware Attention to Speaker Roles and Contexts for Spoken Language Understanding | ||||||||||
| Dlsrl | 7 | 5 years ago | 1 | Python | ||||||
| Deep Bidirection LSTM for Semantic Role Labeling | ||||||||||
| Mcl310 | 6 | 6 years ago | ||||||||
| AWS re:Invent 2017 MCL310 - Building Deep Learning Applications with Apache MXNet and Gluon | ||||||||||
| Deep_pt_srl | 5 | 6 years ago | 1 | bsd-2-clause | Python | |||||
| A deep bi-lstm network for semantic role labeling targeted at the Portuguese Language | ||||||||||
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