Omri Barak
Cognitive Neuroscience · 2007–2013
A researcher in the Science corpus: 4 papers; trusts 13 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 27 citations into it; #1,280 of 10,852 by trust here, #1,166 by citations
- Artificial Intelligence — 16 citations into it; #7,103 of 35,345 by trust here, #5,495 by citations
- Electrical and Electronic Engineering — 16 citations into it; #1,263 of 16,539 by trust here, #3,087 by citations
- Neuroscience — 10 citations into it; #404 of 487 by trust here, #109 by citations
- Optimization & Training — 7 citations into it
- Model Architectures — 5 citations into it
Whom Omri Barak trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David Sussillo
- David J. Willshaw
- Misha Tsodyks
- James Martens
- Geoffrey E. Hinton
- David E. Rumelhart
- Herbert Jaeger
- L. F. Abbott
- John J. Hopfield
- Yoshua Bengio
Who trusts Omri Barak overall
- Stefano Fusi
- Timo Flesch
- Marcus K. Benna
- Guangyu Robert Yang
- H. Francis Song
- G. Huang
- Srdjan Ostojic
- Rafael Yuste
- Jasmine Collins
- N. A. Cayco-Gajic
Papers from Omri Barak's perspective
Ordered by how strongly the researchers Omri Barak trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- The importance of mixed selectivity in complex cognitive tasks (2013) — 1,630 citations
- Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks (2013) — 562 citations
- The Sparseness of Mixed Selectivity Neurons Controls the Generalization-Discrimination Trade-Off (2013) — 230 citations
- Persistent Activity in Neural Networks with Dynamic Synapses (2007) — 137 citations