Michael Eickenberg

Cognitive Neuroscience · with Thirion · 2014–2017

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 33 citations into it; #10,314 of 10,852 by trust here, #4,925 by citations
• Computer Vision and Pattern Recognition — 17 citations into it; #20,895 of 21,575 by trust here, #17,258 by citations
• Neuroscience — 9 citations into it

Whom Michael Eickenberg trusts overall

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

1. John F. Canny
2. Maximilian Riesenhuber
3. Umut Güçlü
4. Nikos K. Logothetis
5. Kendrick Norris Kay
6. Thomas Naselaris
7. Tomaso A. Poggio
8. Pierre Sermanet
9. Thomas Serre
10. Robert Desimone

Who trusts Michael Eickenberg overall

1. Grace W. Lindsay
2. Haiguang Wen
3. Nikolaus Kriegeskorte
4. Charlotte Caucheteux
5. Daniel L. K. Yamins

Papers from Michael Eickenberg's perspective

Ordered by how strongly the researchers Michael Eickenberg 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. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Seeing it all: Convolutional network layers map the function of the human visual system (2017) — 376 citations
• Integrating Multimodal Priors in Predictive Models for the Functional Characterization of Alzheimer's Disease (2015) — 11 citations
• Machine learning for neuroimaging with scikit-learn (2014) — 2,159 citations