Jia Wu
Artificial Intelligence · IEEE Transactions on Knowledge and Data Engineering · 2013–2021
A researcher in the Science corpus: 10 papers; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 143 citations into it
- Statistical and Nonlinear Physics — 81 citations into it
- Information Systems — 46 citations into it
- Computer Vision and Pattern Recognition — 39 citations into it
- Computer Networks and Communications — 37 citations into it
- Graph Learning — 34 citations into it
- Molecular Biology — 27 citations into it
- Representation & Self-Supervised Learning — 25 citations into it
Whom Jia Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Xifeng Yan
- Yoshua Bengio
- Ruslan Salakhutdinov
- Geoffrey E. Hinton
- Jiawei Han
- Diederik P. Kingma
- Alex Krizhevsky
- Tomas Mikolov
- Yann LeCun
- Ilya Sutskever
Who trusts Jia Wu overall
- Qinxue Meng
- Daniel R. Catchpoole
- D. Skillicom
- Aleksandar Bojchevski
- Palash Goyal
- Adamu Ali-Gombe
- Shirui Pan
- Paul J. Kennedy
- Daokun Zhang
- Qi Dong
Papers from Jia Wu's perspective
Ordered by how strongly the researchers Jia Wu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- GENERATIVE ADVERSARIAL NETS
Their papers
- Training deep neural networks on imbalanced data sets (2016) — 452 citations
- Self-adaptive probability estimation for Naive Bayes classification (2013) — 43 citations
- A Comprehensive Survey on Graph Anomaly Detection With Deep Learning (2021) — 830 citations
- A Comprehensive Survey on Community Detection With Deep Learning (2021) — 454 citations
- Multiple Structure-View Learning for Graph Classification (2018) — 75 citations
- Joint structure feature exploration and regularization for multi-task graph classification (2016) — 55 citations
- Tri-Party Deep Network Representation (2016) — 438 citations
- Inferring Latent Network from Cascade Data for Dynamic Social Recommendation (2016) — 13 citations
- Multi-graph-view Learning for Graph Classification (2014) — 52 citations
- Artificial immune system for attribute weighted Naive Bayes classification (2013) — 45 citations