Kevin J. Lang

Statistical and Nonlinear Physics · 1989–2010

A researcher in the Science corpus: 7 papers; trusts 65 researchers and is trusted by 69 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 145 citations into it; #1,636 of 10,127 by trust here, #719 by citations
• Computational Theory and Mathematics — 41 citations into it; #1,481 of 12,182 by trust here, #2,851 by citations
• Computer Networks and Communications — 38 citations into it; #3,165 of 9,886 by trust here, #1,023 by citations
• Molecular Biology — 38 citations into it
• Artificial Intelligence — 34 citations into it; #6,863 of 35,345 by trust here, #14,718 by citations
• Computer Vision and Pattern Recognition — 29 citations into it; #15,518 of 21,575 by trust here, #11,083 by citations
• Geometry and Topology — 22 citations into it
• Algorithms & Complexity — 15 citations into it; #405 of 516 by trust here, #147 by citations

Whom Kevin J. Lang trusts overall

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

1. Fan Chung
2. Mark Newman
3. Peter F. Brown
4. Linyuan Lu
5. Fan Chung Graham
6. Jure Leskovec
7. Geoffrey E. Hinton
8. Michelle Girvan
9. George Karypis
10. Paul J. Werbos

Who trusts Kevin J. Lang overall

1. Jure Leskovec
2. Li Deng
3. Yoshua Bengio
4. Dong Yu
5. Sepp Hochreiter
6. Geoffrey E. Hinton
7. Alex Graves
8. Charles M. Bishop
9. J. Urgen Schmidhuber
10. Evgheniy Faerman

Papers from Kevin J. Lang's perspective

Ordered by how strongly the researchers Kevin J. Lang 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. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Local Graph Partitioning using PageRank Vectors (2006) — 1,111 citations
• Empirical comparison of algorithms for network community detection (2010) — 1,079 citations
• Statistical properties of community structure in large social and information networks (2008) — 866 citations
• Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters (2008) — 2,059 citations
• A time-delay neural network architecture for isolated word recognition (1990)
• Dimensionality Reduction and Prior Knowledge in E-Set Recognition (1989)
• Phoneme recognition using time-delay neural networks (1989)