Weijie Bian
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it
- Computer Vision and Pattern Recognition — 39 citations into it
- Model Architectures — 22 citations into it
- Information Systems — 20 citations into it
- Recommender Systems — 10 citations into it
- Management Science and Operations Research — 8 citations into it
Whom Weijie Bian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Dzmitry Bahdanau
- Alex Graves
- Jimmy Ba
- Yann LeCun
- Ilya Sutskever
Who trusts Weijie Bian overall
Papers from Weijie Bian's perspective
Ordered by how strongly the researchers Weijie Bian 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
- Long Short-Term Memory
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Rocket Launching: A Universal and Efficient Framework for Training Well-performing Light Net (2017) — 129 citations
- Deep Interest Evolution Network for Click-Through Rate Prediction (2018) — 1,336 citations
- Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction (2019) — 332 citations