Yonatan Geifman

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 288 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it; #4,802 of 35,345 by trust here, #10,942 by citations
• Computer Vision and Pattern Recognition — 23 citations into it; #8,202 of 21,575 by trust here, #15,955 by citations
• Model Architectures — 16 citations into it
• Optimization & Training — 8 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Yonatan Geifman trusts overall

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

1. Alex Krizhevsky
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Kaiming He
5. Diederik P. Kingma
6. Barret Zoph
7. Andrew Zisserman
8. Quoc V. Le
9. Yarin Gal
10. Sergey Ioffe

Who trusts Yonatan Geifman overall

1. Erik Jones
2. Tz-Ying Wu
3. Hussein Mozannar
4. Rui Huang
5. Zhizhong Li
6. Ran El-Yaniv
7. Vikash Sehwag
8. Neeraj Varshney
9. Sunil Thulasidasan
10. Akshay Raj Dhamija

Papers from Yonatan Geifman's perspective

Ordered by how strongly the researchers Yonatan Geifman 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Selective Classification for Deep Neural Networks (2017) — 953 citations
• SelectiveNet: A Deep Neural Network with an Integrated Reject Option (2019) — 469 citations
• Deep Active Learning with a Neural Architecture Search (2018) — 50 citations