Doron Haviv

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Optimization & Training — 7 citations into it
• Statistical and Nonlinear Physics — 6 citations into it

Whom Doron Haviv trusts overall

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

1. Naftali Tishby
2. Alex Krizhevsky
3. Yann LeCun
4. Diederik P. Kingma
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Alexander A. Alemi
8. L. V. D. van der Maaten
9. L. Eon Bottou
10. Alessandro Achille

Papers from Doron Haviv's perspective

Ordered by how strongly the researchers Doron Haviv 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. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Direct Validation of the Information Bottleneck Principle for Deep Nets (2019) — 27 citations
• The effectiveness of layer-by-layer training using the information bottleneck principle (2018) — 10 citations