Rongzhi Zhang's repositories
dynamic_social_networks
CSC 555 Social Computing - Project | Social network analysis traditionally makes use of unweighted graphs, with no other information between peers except for acknowledgement of existence of a link. In our work, we attempt to construct a weighted graph using user interactions, where weights represent the degree of recent frequent interaction. We reward the links among users for each interaction and also decay those rewards over time. We therefore, use such recent interactions as evidence of a stronger bond and assign weights accordingly. Finally, we optimize our values of rewards and decay using some power laws which are exhibited by real world weighted networks
Active-NER
Bayesian Deep Active Learning for Named entity recognition (NER)
Active-NLP
Bayesian Deep Active Learning for Natural Language Processing Tasks
Attention-PyTorch
注意力机制实践
awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
bert
TensorFlow code and pre-trained models for BERT
BERT-BiLSTM-CRF-NER
Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services
BERT-NER
Pytorch-Named-Entity-Recognition-with-BERT
HMEAE
Source code for EMNLP-IJCNLP 2019 paper "HMEAE: Hierarchical Modular Event Argument Extraction".
lstm-crf-pytorch
LSTM-CRF in PyTorch
modAL
A modular active learning framework for Python
Named-Entity-Recognition-BidirectionalLSTM-CNN-CoNLL
Keras implementation of "Few-shot Learning for Named Entity Recognition in Medical Text"
Reddit-Roles-Identification
Identify roles of redditors participated in political discussions on Reddit
SLTK
序列化标注工具，基于PyTorch实现BLSTM-CNN-CRF模型，CoNLL 2003 English NER测试集F1值为91.10%（word and char feature）。
Social_networks
Draw graphs of relationships between users based on recursive scraping of follower / following status.
TextFooler
A Model for Natural Language Attack on Text Classification and Inference
transformers
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.