Gehui Shen

Orcid: 0000-0002-2457-3810

According to our database1, Gehui Shen authored at least 15 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Bypassing Logits Bias in Online Class-Incremental Learning with a Generative Framework.
CoRR, 2022

Switch-GPT: An Effective Method for Constrained Text Generation under Few-Shot Settings (Student Abstract).
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Sequence generative adversarial nets with a conditional discriminator.
Neurocomputing, 2021

Towards unsupervised text multi-style transfer with parameter-sharing scheme.
Neurocomputing, 2021

Generative Feature Replay with Orthogonal Weight Modification for Continual Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
A Window-Based Self-Attention approach for sentence encoding.
Neurocomputing, 2020

Learning to compose over tree structures via POS tags for sentence representation.
Expert Syst. Appl., 2020

Self-Supervised Learning Aided Class-Incremental Lifelong Learning.
CoRR, 2020

Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Learning to Compose over Tree Structures via POS Tags.
CoRR, 2018

A Novel Framework for Recurrent Neural Networks with Enhancing Information Processing and Transmission between Units.
CoRR, 2018

TIER: A Novel Model Based on POS Information to Generate Dialogue.
Proceedings of the 5th IEEE International Conference on Cloud Computing and Intelligence Systems, 2018

2017
A Gap-Based Framework for Chinese Word Segmentation via Very Deep Convolutional Networks.
CoRR, 2017

Inter-Weighted Alignment Network for Sentence Pair Modeling.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017


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