Hua Xu

Artificial Intelligence · with Wu · 2020–2022

A researcher in the Science corpus: 3 papers; trusts 55 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #34,011 of 35,345 by trust here, #29,412 by citations
• Computer Vision and Pattern Recognition — 41 citations into it; #20,721 of 21,575 by trust here, #18,782 by citations
• Natural Language Processing — 17 citations into it
• Multimodal Learning — 13 citations into it
• Model Architectures — 10 citations into it
• Signal Processing — 9 citations into it
• Experimental and Cognitive Psychology — 6 citations into it

Whom Hua Xu trusts overall

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

1. Amir Zadeh
2. Geoffrey E. Hinton
3. Sepp Hochreiter
4. Yoshua Bengio
5. J. Urgen Schmidhuber
6. Alex Krizhevsky
7. Diederik P. Kingma
8. Alex Graves
9. Kaiming He
10. Percy Liang

Who trusts Hua Xu overall

1. Wei Han
2. Ankita Gandhi

Papers from Hua Xu's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Consistent Representation Learning for Continual Relation Extraction (2022) — 69 citations
• Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis (2021) — 808 citations
• CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality (2020) — 542 citations