C. Barry
Cognitive Neuroscience · Nature · 2007–2020
A researcher in the Science corpus: 9 papers; trusts 44 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 154 citations into it; #2,505 of 10,852 by trust here, #1,172 by citations
- Cellular and Molecular Neuroscience — 109 citations into it; #617 of 2,998 by trust here, #478 by citations
- Artificial Intelligence — 45 citations into it
- Neuroscience — 37 citations into it
- Model Architectures — 18 citations into it
- Developmental and Educational Psychology — 16 citations into it
- Cognitive Science & Psychology — 11 citations into it
- Cell Biology — 10 citations into it
Whom C. Barry trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Bruce L. McNaughton
- Matthew A. Wilson
- György Buzsáki
- Daniel Bendor
- T. J. Davidson
- Torkel Hafting
- Mark C. Fuhs
- Neil Burgess
- Geoffrey E. Hinton
- David J. Foster
Who trusts C. Barry overall
- Ida Momennejad
- Andrew M. Saxe
- Kristin Andrews
- A. Constantinescu
- Timothy Edward John Behrens
- Karl J. Friston
- Jacob L. S. Bellmund
- Neil Burgess
- Daniel Bush
- Elizabeth S. Spelke
Papers from C. Barry's perspective
Ordered by how strongly the researchers C. Barry trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- Dropout: a simple way to prevent neural networks from overfitting
Their papers
- Vector-based navigation using grid-like representations in artificial agents (2018) — 716 citations
- MEMO: A Deep Network for Flexible Combination of Episodic Memories (2020) — 40 citations
- The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation (2019) — 604 citations
- The Role of Hippocampal Replay in Memory and Planning (2018) — 371 citations
- Hippocampal place cells construct reward related sequences through unexplored space (2015) — 277 citations
- Using Grid Cells for Navigation (2015) — 298 citations
- Grid cell symmetry is shaped by environmental geometry (2015) — 343 citations
- Evidence for grid cells in a human memory network (2010) — 769 citations
- An oscillatory interference model of grid cell firing (2007) — 702 citations