Nicholas Jing Yuan

Artificial Intelligence · 2013–2022

A researcher in the Science corpus: 10 papers; trusts 247 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 239 citations into it; #10,261 of 35,345 by trust here, #7,471 by citations
• Computer Vision and Pattern Recognition — 158 citations into it
• Natural Language Processing — 90 citations into it
• Information Systems — 78 citations into it; #1,599 of 8,771 by trust here, #786 by citations
• Signal Processing — 54 citations into it; #6,340 of 7,572 by trust here, #4,900 by citations
• Management Science and Operations Research — 31 citations into it
• Information Retrieval & Search — 29 citations into it
• Evaluation & Benchmarks — 24 citations into it

Whom Nicholas Jing Yuan trusts overall

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

1. Jing Yuan
2. Yu Zheng
3. Steffen Rendle
4. David M. Blei
5. Geoffrey E. Hinton
6. Peter J. Rousseeuw
7. Yoshua Bengio
8. Diederik P. Kingma
9. Alex Krizhevsky
10. Xing Xie

Who trusts Nicholas Jing Yuan overall

1. Yu Zheng
2. Xiangnan He
3. Hongwei Wang
4. Xiang Wang
5. Qingyao Ai
6. Fuzheng Zhang
7. Yongfeng Zhang
8. Xing Xie
9. Hao Wang
10. Aminu Da’u

Papers from Nicholas Jing Yuan's perspective

Ordered by how strongly the researchers Nicholas Jing Yuan 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Collaborative Knowledge Base Embedding for Recommender Systems (2016) — 1,809 citations
• DRN: A Deep Reinforcement Learning Framework for News Recommendation (2018) — 748 citations
• MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation (2022) — 308 citations
• Multi-Modal Knowledge Graph Construction and Application: A Survey (2022) — 296 citations
• SingGAN: Generative Adversarial Network For High-Fidelity Singing Voice Generation (2021) — 74 citations
• Distant Supervision for Multi-Stage Fine-Tuning in Retrieval-Based Question Answering (2020) — 23 citations
• Collaborative Intent Prediction with Real-Time Contextual Data (2017) — 68 citations
• Discovering Urban Functional Zones Using Latent Activity Trajectories (2015) — 409 citations
• T-Finder: A Recommender System for Finding Passengers and Vacant Taxis (2013) — 443 citations
• Conference on Empirical Methods in Natural Language Processing Proceedings of the Fourth International Workshop on Natural Language Processing for Social Media Socialnlp@emnlp2016 Chairs' Welcome Identifying and Categorizing Disaster-related Tweets Why Do They Leave: Modeling Participation in Online