Nic Ford
Artificial Intelligence · 2019
A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 30 citations into it; #13,680 of 35,345 by trust here, #15,542 by citations
- Safety, Robustness & Interpretability — 24 citations into it; #994 of 2,251 by trust here, #1,349 by citations
- Computer Vision and Pattern Recognition — 11 citations into it
- Signal Processing — 7 citations into it
Whom Nic Ford trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alhussein Fawzi
- Christian Szegedy
- Nicholas Carlini
- Alex Krizhevsky
- Sergey Zagoruyko
- Geoffrey E. Hinton
- Dan Hendrycks
- Kaiming He
- Yash Sharma
- Yoshua Bengio
Who trusts Nic Ford overall
- Raphael Gontijo Lopes
- Ekin Dogus Cubuk
- Evgenia Rusak
- Barret Zoph
- Dong Yin
- Jeremy M. Cohen
- Emin Orhan
- Sylvia J. Smullin
- Daniel Kang
- Angus Galloway
Papers from Nic Ford's perspective
Ordered by how strongly the researchers Nic Ford 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Going deeper with convolutions
Their papers
- Adversarial Examples Are a Natural Consequence of Test Error in Noise (2019) — 343 citations