Jeffrey Heinz

Artificial Intelligence · 2009–2010

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Language and Linguistics — 16 citations into it
• Experimental and Cognitive Psychology — 14 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Natural Language Processing — 5 citations into it

Whom Jeffrey Heinz trusts overall

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

1. Josh Tenenbaum
2. Noam Chomsky
3. Brett Hyde
4. Christopher D. Manning
5. John Shawe-Taylor
6. Leslie G. Valiant
7. Colin Wilson
8. John J. McCarthy
9. Rachel Walker
10. Vladimir Naumovich Vapnik

Papers from Jeffrey Heinz's perspective

Ordered by how strongly the researchers Jeffrey Heinz 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Learning Long-Distance Phonotactics (2010) — 169 citations
• On the role of locality in learning stress patterns* (2009) — 98 citations