Harmanpreet Kaur

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Safety, Robustness & Interpretability — 24 citations into it
• Health Informatics — 7 citations into it

Whom Harmanpreet Kaur trusts overall

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

1. Scott M. Lundberg
2. Cynthia Rudin
3. D. Norman
4. Trevor J. Hastie
5. Robert Tibshirani
6. Jiaming Zeng
7. Su-In Lee
8. Tim Miller
9. Carrie J. Cai
10. Guolin Ke

Who trusts Harmanpreet Kaur overall

1. Han Liu
2. Cynthia Rudin
3. Forough Poursabzi-Sangdeh
4. Q. Liao
5. Vivian Lai
6. Alon Jacovi

Papers from Harmanpreet Kaur's perspective

Ordered by how strongly the researchers Harmanpreet Kaur 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet Large Scale Visual Recognition Challenge
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Interpreting Interpretability: Understanding Data Scientists' Use of Interpretability Tools for Machine Learning (2020) — 609 citations