Marcus K. Benna

Cognitive Neuroscience · 2008–2020

A researcher in the Science corpus: 5 papers; trusts 35 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 41 citations into it; #2,101 of 10,852 by trust here, #3,947 by citations
• Nuclear and High Energy Physics — 33 citations into it; #3,425 of 6,161 by trust here, #3,299 by citations
• Cellular and Molecular Neuroscience — 24 citations into it; #481 of 2,998 by trust here, #1,553 by citations
• Electrical and Electronic Engineering — 18 citations into it; #2,242 of 16,539 by trust here, #7,640 by citations
• Astronomy and Astrophysics — 16 citations into it; #6,302 of 10,964 by trust here, #6,742 by citations
• Statistical and Nonlinear Physics — 16 citations into it; #4,966 of 10,127 by trust here, #2,631 by citations
• Artificial Intelligence — 14 citations into it
• Neuroscience — 12 citations into it; #152 of 487 by trust here, #276 by citations

Whom Marcus K. Benna trusts overall

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

1. Stefano Fusi
2. Wickliffe C. Abraham
3. J. Schwarz
4. Andreas Gustavsson
5. J. Bagger
6. John T. Wixted
7. Alex Roxin
8. Georgios Papadopoulos
9. Seok Kim
10. Timothy F. Brady

Who trusts Marcus K. Benna overall

1. Pascal Leimer
2. Christos Kaplanis
3. D. Gaiotto
4. Michael H. Herzog
5. Paul Smolen
6. S. Giombi
7. Vincenzo Lomonaco
8. D. Berenstein
9. A. Hanany
10. F. Benini

Papers from Marcus K. Benna's perspective

Ordered by how strongly the researchers Marcus K. Benna 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. Gradient-based learning applied to document recognition
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Computational principles of synaptic memory consolidation (2016) — 246 citations
• Computational principles of biological memory (2015) — 17 citations
• The geometry of abstraction in hippocampus and prefrontal cortex (2020) — 432 citations
• Charges of monopole operators in Chern-Simons Yang-Mills theory (2009) — 136 citations
• Superconformal Chern-Simons Theories and AdS(4)/CFT(3) Correspondence (2008) — 501 citations