Ruihua Song
Artificial Intelligence · 2004–2022
A researcher in the Science corpus: 8 papers; trusts 164 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 386 citations into it
- Computer Vision and Pattern Recognition — 220 citations into it; #12,935 of 21,575 by trust here, #6,426 by citations
- Natural Language Processing — 125 citations into it
- Information Systems — 51 citations into it; #4,361 of 8,771 by trust here, #3,640 by citations
- Information Retrieval & Search — 10 citations into it
- Recommender Systems — 10 citations into it
- Statistical and Nonlinear Physics — 5 citations into it
Whom Ruihua Song trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ilya Sutskever
- Taher H. Haveliwala
- Xuehua Shen
- Lan Yi
- Yoshua Bengio
- Bin Tan
- Diederik P. Kingma
- Kaiming He
- Vladimir Naumovich Vapnik
Who trusts Ruihua Song overall
- Fabrizio Silvestri
- Wei David Liu
- Wai Lam
- Zaiqing Nie
- Jordan L. Boyd-Graber
- Xiaofeng Meng
- Christopher C. Yang
- Paul N. Bennett
Papers from Ruihua Song's perspective
Ordered by how strongly the researchers Ruihua Song trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Pre-Trained Models: Past, Present and Future (2021) — 1,095 citations
- WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training (2021) — 146 citations
- Learning block importance models for web pages (2004) — 316 citations
- AdaSpeech 4: Adaptive Text to Speech in Zero-Shot Scenarios (2022) — 78 citations
- Self-supervised Context-aware Style Representation for Expressive Speech Synthesis (2022) — 17 citations
- Towards artificial general intelligence via a multimodal foundation model (2021) — 331 citations
- Personalized Reason Generation for Explainable Song Recommendation (2019) — 53 citations
- A large-scale evaluation and analysis of personalized search strategies (2007) — 703 citations