Will Y. Zou
Computer Vision and Pattern Recognition · 2011–2014
A researcher in the Science corpus: 5 papers; trusts 434 researchers and is trusted by 2,275 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 84 citations into it; #834 of 21,575 by trust here, #2,836 by citations
- Artificial Intelligence — 41 citations into it; #2,770 of 35,345 by trust here, #3,338 by citations
- Representation & Self-Supervised Learning — 37 citations into it; #500 of 3,145 by trust here, #657 by citations
- Natural Language Processing — 21 citations into it; #2,085 of 5,688 by trust here, #1,975 by citations
- Cognitive Neuroscience — 18 citations into it
- Model Architectures — 13 citations into it
- Optimization & Training — 12 citations into it
- Aerospace Engineering — 11 citations into it
Whom Will Y. Zou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Andrew Y. Ng
- Yann LeCun
- Alex Krizhevsky
- David G. Lowe
- Honglak Lee
- Quoc V. Le
- Ronan Collobert
- Ross B. Girshick
Who trusts Will Y. Zou overall
- Yoshua Bengio
- Dinesh Jayaraman
- Kristen Grauman
- Quoc V. Le
- Davide Maltoni
- X. Wang
- Ruohan Gao
- Abhinav Kumar Gupta
- Kyunghyun Cho
- Aaron C. Courville
Papers from Will Y. Zou's perspective
Ordered by how strongly the researchers Will Y. Zou 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
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis (2011) — 1,119 citations
- Deep Learning of Invariant Features via Simulated Fixations in Video (2012) — 173 citations
- Bilingual Word Embeddings for Phrase-Based Machine Translation (2013) — 581 citations
- Generic Object Detection with Dense Neural Patterns and Regionlets (2014) — 67 citations
- Unsupervised learning of visual invariance with temporal coherence (2011) — 56 citations