Edward Chou
Artificial Intelligence · 2018
A researcher in the Science corpus: 3 papers; trusts 336 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 102 citations into it; #34,096 of 35,345 by trust here, #19,873 by citations
- Safety, Robustness & Interpretability — 62 citations into it; #1,661 of 2,251 by trust here, #1,512 by citations
- Computer Vision and Pattern Recognition — 60 citations into it; #15,752 of 21,575 by trust here, #11,950 by citations
- Signal Processing — 25 citations into it
- Model Architectures — 19 citations into it
- Privacy & Security — 17 citations into it
- Hardware and Architecture — 9 citations into it
- Computational Theory and Mathematics — 7 citations into it
Whom Edward Chou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Karen Simonyan
- Ross B. Girshick
- Yann LeCun
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Ian J. Goodfellow
- Andrew Zisserman
- Christian Szegedy
Who trusts Edward Chou overall
- Eugene Bagdasarian
- Di Tang
- M. Sadegh Riazi
- Yiming Li
- Baoyuan Wu
- Yuezun Li
- Yansong Gao
- Lingjuan Lyu
- Vitaly Shmatikov
- Xiaojun Xu
Papers from Edward Chou's perspective
Ordered by how strongly the researchers Edward Chou 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
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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
- SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems (2018) — 352 citations
- Faster CryptoNets: Leveraging Sparsity for Real-World Encrypted Inference (2018) — 228 citations
- SentiNet: Detecting Physical Attacks Against Deep Learning Systems (2018) — 111 citations