Nianzu Ma

Artificial Intelligence · 2015–2021

A researcher in the Science corpus: 6 papers; trusts 187 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 166 citations into it; #6,912 of 35,345 by trust here, #11,750 by citations
• Natural Language Processing — 94 citations into it
• Computer Vision and Pattern Recognition — 49 citations into it
• Meta & Continual Learning — 41 citations into it; #191 of 1,041 by trust here, #361 by citations
• Representation & Self-Supervised Learning — 41 citations into it; #2,065 of 3,145 by trust here, #2,863 by citations
• Information Systems — 17 citations into it
• Reinforcement Learning — 14 citations into it
• Graph Learning — 12 citations into it

Whom Nianzu Ma trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Ilya Sutskever
4. Tomas Mikolov
5. Alex Krizhevsky
6. Sepp Hochreiter
7. Diederik P. Kingma
8. Antoine Bordes
9. Jason Aaron Edward Weston
10. Yann LeCun

Who trusts Nianzu Ma overall

1. Bing Liu
2. Zixuan Ke
3. Shuai Wang
4. Sahisnu Mazumder
5. Lei Shu
6. Qi Qin
7. Zhiyuan Chen
8. Hu Xu
9. Gyuhak Kim
10. B. Liu

Papers from Nianzu Ma's perspective

Ordered by how strongly the researchers Nianzu Ma trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Towards a Continuous Knowledge Learning Engine for Chatbots (2018) — 23 citations
• Lifelong Learning for Sentiment Classification (2015) — 159 citations
• Achieving Forgetting Prevention and Knowledge Transfer in Continual Learning (2021) — 159 citations
• Continuous and Interactive Factual Knowledge Learning in Verification Dialogues (2020)
• Forward and Backward Knowledge Transfer for Sentiment Classification (2019) — 18 citations
• Lifelong and Interactive Learning of Factual Knowledge in Dialogues (2019) — 28 citations