Gal Elidan

Artificial Intelligence · 2001–2022

A researcher in the Science corpus: 8 papers; trusts 80 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it; #10,799 of 35,345 by trust here, #15,004 by citations
• Computer Vision and Pattern Recognition — 51 citations into it; #15,779 of 21,575 by trust here, #8,612 by citations
• Probabilistic & Bayesian Methods — 17 citations into it
• Optimization & Training — 11 citations into it
• Management Science and Operations Research — 8 citations into it
• Statistical Learning Theory — 7 citations into it
• Statistics and Probability — 7 citations into it; #3,343 of 12,932 by trust here, #9,714 by citations
• Computer Networks and Communications — 6 citations into it; #2,391 of 9,886 by trust here, #4,594 by citations

Whom Gal Elidan trusts overall

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

1. Christopher K. I. Williams
2. Robert Tibshirani
3. Andrew Gordon Wilson
4. Dimitri P. Bertsekas
5. Judea Pearl
6. Iain Murray
7. Alan L. Yuille
8. Geoffrey E. Hinton
9. Zoubin Ghahramani
10. David John Cameron MacKay

Who trusts Gal Elidan overall

1. Yucheng Low
2. Joseph E. Gonzalez
3. George Papamakarios
4. David Salinas
5. Sebastian Nowozin
6. Lorenzo Torresani
7. David Lopez-Paz
8. Yang Song
9. Stéphane Ross
10. Carlos Guestrin

Papers from Gal Elidan's perspective

Ordered by how strongly the researchers Gal Elidan 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. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Multi-Class Segmentation with Relative Location Prior (2008) — 463 citations
• Residual Belief Propagation: Informed Scheduling for Asynchronous Message Passing (2006) — 315 citations
• Explaining in Style: Training a GAN to explain a classifier in StyleSpace (2021) — 184 citations
• Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning (2022) — 13 citations
• Scalable Learning of Non-Decomposable Objectives (2016) — 122 citations
• Inferring subnetworks from perturbed expression profiles (2001) — 622 citations
• Copulas in Machine Learning (2013) — 73 citations
• Improper Deep Kernels (2016) — 10 citations