Gerald Penn
Artificial Intelligence · 2009–2014
A researcher in the Science corpus: 5 papers; trusts 45 researchers and is trusted by 102 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 41 citations into it; #2,353 of 35,345 by trust here, #3,080 by citations
- Signal Processing — 30 citations into it; #363 of 7,572 by trust here, #255 by citations
- Natural Language Processing — 21 citations into it; #2,799 of 5,688 by trust here, #5,214 by citations
- Computer Vision and Pattern Recognition — 19 citations into it
- Speech & Audio — 13 citations into it; #122 of 1,076 by trust here, #122 by citations
Whom Gerald Penn trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Abdel-rahman Mohamed
- George E. Dahl
- Yann LeCun
- Yoshua Bengio
- Dong Yu
- Li Deng
- Chin-Yew Lin
- Alex Krizhevsky
- Peter D. Turney
Who trusts Gerald Penn overall
- Dong Yu
- Li Deng
- Jinyu Li
- Tara N. Sainath
- Ossama Abdel-Hamid
- Geoffrey E. Hinton
- Abdel-rahman Mohamed
- Karol J. Piczak
- Abigail See
- Hank Liao
Papers from Gerald Penn's perspective
Ordered by how strongly the researchers Gerald Penn 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Applying Convolutional Neural Networks concepts to hybrid NN-HMM model for speech recognition (2012) — 942 citations
- Convolutional Neural Networks for Speech Recognition (2014) — 2,165 citations
- Understanding how Deep Belief Networks perform acoustic modelling (2012) — 322 citations
- Unsupervised Sentence Enhancement for Automatic Summarization (2014) — 41 citations
- Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations (2009) — 365 citations