Yair Be’ery
Artificial Intelligence · 2016–2017
A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 19 citations into it
- Computer Vision and Pattern Recognition — 13 citations into it
- Natural Language Processing — 7 citations into it
- Electrical and Electronic Engineering — 6 citations into it
- Computer Networks and Communications — 5 citations into it; #3,034 of 9,886 by trust here, #5,518 by citations
Whom Yair Be’ery trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- T. Richardson
- Alex Graves
- Yoshua Bengio
- Rüdiger L. Urbanke
- Matthew D. Zeiler
- Diederik P. Kingma
- Alex Krizhevsky
- Abdel-rahman Mohamed
Who trusts Yair Be’ery overall
Papers from Yair Be’ery's perspective
Ordered by how strongly the researchers Yair Be’ery trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Understanding the difficulty of training deep feedforward neural networks
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Learning to decode linear codes using deep learning (2016) — 521 citations
- Deep Learning Methods for Improved Decoding of Linear Codes (2017) — 552 citations