David W. Zhang
Artificial Intelligence · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 202 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 51 citations into it
- Computer Vision and Pattern Recognition — 43 citations into it
- Model Architectures — 24 citations into it
- Optimization & Training — 14 citations into it
- Generative Models — 10 citations into it
- Probabilistic & Bayesian Methods — 9 citations into it
- Representation & Self-Supervised Learning — 9 citations into it
- Natural Language Processing — 7 citations into it
Whom David W. Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yann LeCun
- Yoshua Bengio
- Alex Krizhevsky
- Oriol Vinyals
- Yan Zhang
- Ilya Sutskever
Who trusts David W. Zhang overall
Papers from David W. Zhang's perspective
Ordered by how strongly the researchers David W. Zhang 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
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Set Prediction without Imposing Structure as Conditional Density Estimation (2020) — 19 citations
- Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation (2021) — 22 citations