Xu Chen
Artificial Intelligence · with Zhang · 2016–2021
A researcher in the Science corpus: 11 papers; trusts 437 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 312 citations into it; #5,787 of 35,345 by trust here, #5,028 by citations
- Information Systems — 285 citations into it; #694 of 8,771 by trust here, #403 by citations
- Computer Vision and Pattern Recognition — 128 citations into it; #7,566 of 21,575 by trust here, #6,206 by citations
- Natural Language Processing — 83 citations into it
- Recommender Systems — 75 citations into it; #149 of 233 by trust here, #130 by citations
- Management Science and Operations Research — 50 citations into it
- Representation & Self-Supervised Learning — 35 citations into it
- Model Architectures — 31 citations into it
Whom Xu Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Julian McAuley
- Geoffrey E. Hinton
- Yongfeng Zhang
- Ruslan Salakhutdinov
- Yoshua Bengio
- Alex Krizhevsky
- Ilya Sutskever
- Diederik P. Kingma
- Steffen Rendle
- Alex Graves
Who trusts Xu Chen overall
- Yongfeng Zhang
- Xiangnan He
- Hanxiong Chen
- Hongteng Xu
- Qingyao Ai
- Krisztian Balog
- Jiaxi Tang
- Roberto Confalonieri
- Xiang Wang
- Zheng Qin
Papers from Xu Chen's perspective
Ordered by how strongly the researchers Xu Chen trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Generate Natural Language Explanations for Recommendation (2021) — 70 citations
- Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network: Towards Visually Explainable Recommendation (2019) — 358 citations
- Dynamic Explainable Recommendation Based on Neural Attentive Models (2019) — 142 citations
- Explainable Recommendation: A Survey and New Perspectives (2018) — 1,163 citations
- Adversarial Distillation for Efficient Recommendation with External Knowledge (2018) — 62 citations
- Towards Conversational Search and Recommendation: System Ask, User Respond (2018) — 451 citations
- Learning over Knowledge-Base Embeddings for Recommendation (2018) — 379 citations
- Sequential Recommendation with User Memory Networks (2018) — 544 citations
- Visually Explainable Recommendation (2018) — 54 citations
- Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources (2017) — 332 citations
- Learning to Rank Features for Recommendation over Multiple Categories (2016) — 162 citations