Pascal Mamassian

Cognitive Neuroscience · 2004–2021

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 21 citations into it; #1,309 of 10,852 by trust here, #2,494 by citations
• Computer Vision and Pattern Recognition — 14 citations into it; #5,470 of 21,575 by trust here, #6,671 by citations
• Artificial Intelligence — 6 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom Pascal Mamassian trusts overall

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

1. David Mumford
2. Paul A. Viola
3. Vladimir Naumovich Vapnik
4. Tomaso A. Poggio
5. Song-Chun Zhu
6. Eric R. Ziegel
7. James O. Berger
8. Geoffrey E. Hinton
9. Yoav Freund
10. Josh Tenenbaum

Who trusts Pascal Mamassian overall

1. Karl J. Friston
2. Moshe Bar
3. Michael Tarr
4. Aaron Hertzmann
5. Konrad Paul Kording
6. Elizabeth Pellicano
7. Kelsey R. Allen
8. Adam N. Sanborn
9. H. D. den Ouden
10. Rubén Moreno-Bote

Papers from Pascal Mamassian's perspective

Ordered by how strongly the researchers Pascal Mamassian 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. Going deeper with convolutions

Their papers

• Object perception as Bayesian inference. (2004) — 1,303 citations
• Faculty Opinions recommendation of Learning orthogonalizes visual cortical population codes. (2021)