Christopher Summerfield
Cognitive Neuroscience · 2007–2023
A researcher in the Science corpus: 18 papers; trusts 153 researchers and is trusted by 51 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 326 citations into it; #591 of 10,852 by trust here, #529 by citations
- Artificial Intelligence — 184 citations into it; #34,239 of 35,345 by trust here, #3,072 by citations
- Computer Vision and Pattern Recognition — 102 citations into it
- Neuroscience — 79 citations into it; #434 of 487 by trust here, #178 by citations
- Cellular and Molecular Neuroscience — 49 citations into it
- Reinforcement Learning — 47 citations into it
- Electrical and Electronic Engineering — 41 citations into it; #15,794 of 16,539 by trust here, #1,993 by citations
- Cognitive Science & Psychology — 37 citations into it
Whom Christopher Summerfield trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Karl J. Friston
- Geoffrey E. Hinton
- Andrew Barto
- John S. Duncan
- Alex Graves
- Richard S. Sutton
- Yoshua Bengio
- David Mumford
- Peter S. Dayan
- Alex Krizhevsky
Who trusts Christopher Summerfield overall
- Peter Kok
- Jorie Koster-Hale
- Janneke F. M. Jehee
- Xing Tian
- James C. R. Whittington
- Floris P. de Lange
- F. D. de Lange
- Matthew Botvinick
- Gregory Hickok
- H. D. den Ouden
Papers from Christopher Summerfield's perspective
Ordered by how strongly the researchers Christopher Summerfield 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)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Hybrid computing using a neural network with dynamic external memory (2016) — 1,765 citations
- Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017 (2017) — 38 citations
- Fine-tuning language models to find agreement among humans with diverse preferences (2022) — 336 citations
- Using the Veil of Ignorance to align AI systems with principles of justice (2023) — 47 citations
- Orthogonal representations for robust context-dependent task performance in brains and neural networks (2022) — 194 citations
- If deep learning is the answer, what is the question? (2020) — 325 citations
- Comparing continual task learning in minds and machines (2018) — 156 citations
- Selective overweighting of larger magnitudes during noisy numerical comparison (2017) — 72 citations
- Confidence matching in group decision-making (2017) — 135 citations
- Neuroscience-Inspired Artificial Intelligence. (2017) — 1,404 citations
- Economic irrationality is optimal during noisy decision making (2016) — 116 citations
- Expectation in perceptual decision making: neural and computational mechanisms (2014) — 781 citations
- Concurrent Repetition Enhancement and Suppression Responses in Extrastriate Visual Cortex (2012) — 86 citations
- Metacognition in human decision-making: confidence and error monitoring (2012) — 626 citations
- Expectation and Surprise Determine Neural Population Responses in the Ventral Visual Stream (2010) — 359 citations
- Expectation (and attention) in visual cognition. (2009) — 954 citations
- Neural repetition suppression reflects fulfilled perceptual expectations (2008) — 721 citations
- An information theoretical approach to prefrontal executive function. (2007) — 1,090 citations