W. Ronny Huang
Artificial Intelligence · 2018–2021
A researcher in the Science corpus: 6 papers; trusts 66 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 143 citations into it; #35,085 of 35,345 by trust here, #13,544 by citations
- Safety, Robustness & Interpretability — 77 citations into it; #1,736 of 2,251 by trust here, #611 by citations
- Computer Vision and Pattern Recognition — 53 citations into it; #21,487 of 21,575 by trust here, #18,266 by citations
- Signal Processing — 36 citations into it
- Optimization & Training — 20 citations into it
- Natural Language Processing — 12 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
Whom W. Ronny Huang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Kaiming He
- Yoshua Bengio
- Christian Szegedy
- Nicholas Carlini
- Yann LeCun
- Ilya Sutskever
- Peter L. Bartlett
Who trusts W. Ronny Huang overall
- Zhiyi Tian
- Eric Wallace
- Micah Goldblum
- Alexander Wan
- Wesley J. Maddox
- Lei Cui
- Vale Tolpegin
- Han Xu
- Nicholas Carlini
- Dimitris Tsipras
Papers from W. Ronny Huang's perspective
Ordered by how strongly the researchers W. Ronny Huang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- 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
- Scaling End-to-End Models for Large-Scale Multilingual ASR (2021) — 86 citations
- MetaPoison: Practical General-purpose Clean-label Data Poisoning (2020) — 237 citations
- Understanding Generalization through Visualizations (2019) — 93 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