Michael N. Jones

Artificial Intelligence · 2007–2015

A researcher in the Science corpus: 3 papers; trusts 26 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it; #6,973 of 35,345 by trust here, #16,166 by citations
• Natural Language Processing — 25 citations into it
• Cognitive Neuroscience — 18 citations into it
• Developmental and Educational Psychology — 13 citations into it; #764 of 8,223 by trust here, #2,529 by citations
• Representation & Self-Supervised Learning — 13 citations into it
• Cognitive Science & Psychology — 8 citations into it
• Neuroscience — 6 citations into it
• Model Architectures — 5 citations into it

Whom Michael N. Jones trusts overall

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

1. Jeffrey L. Elman
2. T. Landauer
3. Peter D. Turney
4. Dekang Lin
5. Tony A. Plate
6. Pentti Kanerva
7. Stephen Grossberg
8. David E. Rumelhart
9. Marc W Howard
10. Geoffrey E. Hinton

Who trusts Michael N. Jones overall

1. K. Erk
2. Jeff Mitchell
3. Alessandro Lenci
4. Timo Honkela
5. Eric Crawford
6. Thomas T. Hills
7. Paul Michel Bernard Verhaeghen
8. Fabio Massimo Zanzotto
9. Siddhartha R. Jonnalagadda
10. Justin Garten

Papers from Michael N. Jones's perspective

Ordered by how strongly the researchers Michael N. Jones trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. A Solution to Plato's Problem: The Latent Semantic Analysis Theory of Acquisition, Induction, and Representation of Knowledge.
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Representing word meaning and order information in a composite holographic lexicon. (2007) — 632 citations
• Optimal foraging in semantic memory. (2012) — 400 citations
• Models of Semantic Memory (2015) — 191 citations