Melih Elibol

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 11 citations into it; #15,790 of 35,345 by trust here, #21,878 by citations
• Optimization & Training — 9 citations into it

Whom Melih Elibol trusts overall

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

1. Matthias Feurer
2. Jost Tobias Springenberg
3. Neil D. Lawrence
4. Lisha Li
5. Jasper Snoek
6. Frank Hutter
7. James Bergstra
8. Yoshua Bengio
9. Isabelle M Guyon
10. Geoffrey E. Hinton

Who trusts Melih Elibol overall

1. Joaquin Vanschoren
2. Laura Gustafson
3. Yolanda Gil
4. Valerio Perrone

Papers from Melih Elibol's perspective

Ordered by how strongly the researchers Melih Elibol trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Learning Multiple Layers of Features from Tiny Images
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Practical Bayesian Optimization of Machine Learning Algorithms
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Probabilistic Matrix Factorization for Automated Machine Learning (2017) — 146 citations
• Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs (2018) — 300 citations