Ali Shafahi
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 6 papers; trusts 132 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 159 citations into it
- Safety, Robustness & Interpretability — 139 citations into it; #1,894 of 2,251 by trust here, #419 by citations
- Computer Vision and Pattern Recognition — 65 citations into it
- Signal Processing — 32 citations into it
- Hardware and Architecture — 20 citations into it
- Model Architectures — 12 citations into it
- Optimization & Training — 9 citations into it
Whom Ali Shafahi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Ian J. Goodfellow
- Nicholas Carlini
- Christian Szegedy
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Alexey Kurakin
- Ilya Sutskever
- Yoshua Bengio
Who trusts Ali Shafahi overall
- Tianyu Pang
- Han Xu
- Chen Zhu
- Micah Goldblum
- Cihang Xie
- W. Ronny Huang
- Evgenia Rusak
- Xiao Yang
- Nicholas Carlini
- Elvis Dohmatob
Papers from Ali Shafahi's perspective
Ordered by how strongly the researchers Ali Shafahi 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Universal Adversarial Training (2018) — 211 citations
- Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training? (2019) — 44 citations
- Adversarial Training for Free! (2019) — 1,469 citations
- Transferable Clean-Label Poisoning Attacks on Deep Neural Nets (2019) — 327 citations
- Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks (2018) — 1,286 citations
- Are adversarial examples inevitable? (2018) — 305 citations