Zhihao Yang
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 4 papers; trusts 16 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 44 citations into it; #31,543 of 35,345 by trust here, #25,040 by citations
- Natural Language Processing — 25 citations into it
- Molecular Biology — 19 citations into it; #14,383 of 17,773 by trust here, #13,563 by citations
- Representation & Self-Supervised Learning — 15 citations into it
- Optimization & Training — 7 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Zhihao Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Tomas Mikolov
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Diederik P. Kingma
- Richard Socher
- Hugo Larochelle
- Thomas G. Dietterich
Who trusts Zhihao Yang overall
Papers from Zhihao Yang's perspective
Ordered by how strongly the researchers Zhihao Yang 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)
- 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Drug drug interaction extraction from biomedical literature using syntax convolutional neural network (2016) — 192 citations
- BioWordVec, improving biomedical word embeddings with subword information and MeSH (2019) — 497 citations
- DUTIR in BioNLP-ST 2016: Utilizing Convolutional Network and Distributed Representation to Extract Complicate Relations (2016) — 12 citations
- An attention‐based BiLSTM‐CRF approach to document‐level chemical named entity recognition (2018) — 386 citations