Momin M. Malik

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 3 papers; trusts 103 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it; #29,630 of 35,345 by trust here, #32,362 by citations
• Statistics and Probability — 39 citations into it
• Statistical and Nonlinear Physics — 29 citations into it; #6,855 of 10,127 by trust here, #8,981 by citations
• Sociology and Political Science — 28 citations into it
• Economics and Econometrics — 18 citations into it
• Safety, Robustness & Interpretability — 18 citations into it
• AI Ethics, Fairness & Society — 13 citations into it
• Evaluation & Benchmarks — 13 citations into it

Whom Momin M. Malik trusts overall

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

1. Yehuda Koren
2. David Ruppert
3. Kelly Hannah-Moffat
4. Alan Mislove
5. Brent J. Hecht
6. R. Caruana
7. Roger S. Bivand
8. Leo Breiman
9. Benjamin Letham
10. M. Delgado

Who trusts Momin M. Malik overall

1. I. Anderson
2. Wendy Wood
3. Sayash Kapoor
4. Inioluwa Deborah Raji
5. Zeerak Talat
6. Reva Schwartz
7. Jürgen Pfeffer

Papers from Momin M. Malik's perspective

Ordered by how strongly the researchers Momin M. Malik 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Hierarchy of Limitations in Machine Learning (2020) — 75 citations
• Identifying Platform Effects in Social Media Data (2016) — 57 citations
• Population Bias in Geotagged Tweets (2015) — 170 citations