Jeff Hawkins
Cognitive Neuroscience · 2006–2022
A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 36 citations into it; #4,124 of 10,852 by trust here, #7,130 by citations
- Cellular and Molecular Neuroscience — 23 citations into it; #1,090 of 2,998 by trust here, #2,919 by citations
- Artificial Intelligence — 20 citations into it; #33,877 of 35,345 by trust here, #23,077 by citations
- Computer Vision and Pattern Recognition — 14 citations into it
- Neuroscience — 11 citations into it
- Electrical and Electronic Engineering — 7 citations into it; #5,755 of 16,539 by trust here, #15,621 by citations
- Model Architectures — 7 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
Whom Jeff Hawkins trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Lawrence R. Rabiner
- Karl J. Friston
- Teuvo Kohonen
- Matthew E. Larkum
- Barbara Olshausen
- Yann LeCun
- Maximilian Riesenhuber
- Biing-Hwang Fred Juang
- Geoffrey E. Hinton
- Li Fei-Fei
Who trusts Jeff Hawkins overall
- Dileep George
- Bo Chen
- Adam Henry Marblestone
- J. Urgen Schmidhuber
- Subutai Ahmad
- Greg Wayne
- Alexander Lavin
- Seth D. Baum
- Konrad Paul Kording
- Scott Purdy
Papers from Jeff Hawkins's perspective
Ordered by how strongly the researchers Jeff Hawkins trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- 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)
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Towards a Mathematical Theory of Cortical Micro-circuits (2009) — 446 citations
- Why Neurons Have Thousands of Synapses, a Theory of Sequence Memory in Neocortex (2015) — 436 citations
- Catalyzing next-generation Artificial Intelligence through NeuroAI (2022) — 299 citations
- Special report : Can we copy the brain? - What intelligent machines need to learn from the Neocortex (2017) — 41 citations
- Hierarchical Temporal Memory Concepts , Theory , and Terminology (2006)