Yoav Chai

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 39 citations into it
• Computer Vision and Pattern Recognition — 26 citations into it
• Natural Language Processing — 11 citations into it
• Safety, Robustness & Interpretability — 11 citations into it
• Model Architectures — 7 citations into it
• Signal Processing — 6 citations into it

Whom Yoav Chai trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Sepp Hochreiter
4. Kyunghyun Cho
5. Dzmitry Bahdanau
6. Alex Krizhevsky
7. Yann LeCun
8. Diederik P. Kingma
9. Ian J. Goodfellow
10. J. Urgen Schmidhuber

Papers from Yoav Chai's perspective

Ordered by how strongly the researchers Yoav Chai trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks (2019) — 56 citations
• NICE: Noise Injection and Clamping Estimation for Neural Network Quantization (2018) — 68 citations