Zhizhen Zhao
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 34 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 41 citations into it; #25,214 of 35,345 by trust here, #19,439 by citations
- Graph Learning — 26 citations into it
- Computer Vision and Pattern Recognition — 22 citations into it; #15,531 of 21,575 by trust here, #12,419 by citations
- Representation & Self-Supervised Learning — 16 citations into it
- Computational Mechanics — 9 citations into it
- Computational Theory and Mathematics — 9 citations into it
- Molecular Biology — 8 citations into it
- Signal Processing — 8 citations into it; #6,863 of 7,572 by trust here, #6,355 by citations
Whom Zhizhen Zhao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
- Alex Graves
- Alex Krizhevsky
- Amit Singer
- Oriol Vinyals
- Max Welling
Who trusts Zhizhen Zhao overall
- William L. Hamilton
- Seyed Mehran Kazemi
- Arvid Lundervold
- Si Zhang
- Filippo Maria Bianchi
- Jerret Ross
- Ken Ziyu Liu
- Felix Wu
Papers from Zhizhen Zhao's perspective
Ordered by how strongly the researchers Zhizhen Zhao 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
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- LanczosNet: Multi-Scale Deep Graph Convolutional Networks (2019) — 249 citations
- Denoising Gravitational Waves with Enhanced Deep Recurrent Denoising Auto-encoders (2017) — 70 citations
- Bispectrum Inversion with Application to Multireference Alignment (2017) — 107 citations