D. Johnson
Experimental and Cognitive Psychology · with Borden · 2009–2020
A researcher in the Science corpus: 6 papers; trusts 35 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Experimental and Cognitive Psychology — 45 citations into it; #3,664 of 9,731 by trust here, #7,077 by citations
- Social Psychology — 37 citations into it; #3,795 of 15,694 by trust here, #8,056 by citations
- Cognitive Neuroscience — 31 citations into it
- Literature and Literary Theory — 13 citations into it; #744 of 2,496 by trust here, #728 by citations
- Artificial Intelligence — 9 citations into it
- Clinical Psychology — 9 citations into it; #2,760 of 8,024 by trust here, #6,527 by citations
- Education — 9 citations into it
- Developmental and Educational Psychology — 6 citations into it
Whom D. Johnson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Paul J Silvia
- Raymond A. Mar
- Roger E. Beaty
- Suzanne Keen
- Geoff Cumming
- Maciej Karwowski
- Yves Rosseel
- Adam E. Green
- Keith Oatley
- Jean Decety
Who trusts D. Johnson overall
- E. Koopman
- Jutta Joormann
- Jesse J. Chandler
- S. Scheibe
- Josh M. Cisler
- Gijsbert Stoet
- Maja Djikic
- D. Shapiro
- Melissa G. Keith
Papers from D. Johnson's perspective
Ordered by how strongly the researchers D. Johnson trusts endorse each paper. Same corpus, a different order for every researcher.
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
- GloVe: Global Vectors for Word Representation
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Long Short-Term Memory
- Making creative metaphors: The importance of fluid intelligence for creative thought
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Understanding the New Statistics: Effect Sizes, Confidence Intervals, and Meta-Analysis
- Gradient-based learning applied to document recognition
- Vector-based Models of Semantic Composition
Their papers
- Goal-directed attentional deployment to emotional faces and individual differences in emotional regulation (2009) — 103 citations
- Transportation into a story increases empathy, prosocial behavior, and perceptual bias toward fearful expressions (2012) — 286 citations
- Automating creativity assessment with SemDis: An open platform for computing semantic distance (2020) — 296 citations
- Potentiating empathic growth: Generating imagery while reading fiction increases empathy and prosocial behavior. (2013) — 94 citations
- Reading Narrative Fiction Reduces Arab-Muslim Prejudice and Offers a Safe Haven From Intergroup Anxiety (2013) — 105 citations
- Participants at Your Fingertips (2012) — 92 citations