Badri N. Patro

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 529 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 86 citations into it; #19,706 of 35,345 by trust here, #26,682 by citations
• Computer Vision and Pattern Recognition — 83 citations into it; #12,329 of 21,575 by trust here, #17,258 by citations
• Multimodal Learning — 37 citations into it
• Natural Language Processing — 20 citations into it
• Meta & Continual Learning — 16 citations into it
• Representation & Self-Supervised Learning — 13 citations into it
• Probabilistic & Bayesian Methods — 9 citations into it
• Safety, Robustness & Interpretability — 9 citations into it

Whom Badri N. Patro trusts overall

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

1. Yarin Gal
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ilya Sutskever
5. Kaiming He
6. Yoshua Bengio
7. Diederik P. Kingma
8. Yann LeCun
9. Oriol Vinyals
10. Ross B. Girshick

Who trusts Badri N. Patro overall

1. Vinod Kumar Kurmi
2. Peng-Tao Jiang
3. Vinay P. Namboodiri
4. Shanu Kumar
5. Mayank Lunayach
6. Moloud Abdar
7. Liyuan Wang
8. Dan Guo
9. Shivansh Patel
10. Haoxuan Qu

Papers from Badri N. Patro's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Differential Attention for Visual Question Answering (2018) — 79 citations
• Do not Forget to Attend to Uncertainty while Mitigating Catastrophic Forgetting (2021) — 26 citations
• U-CAM: Visual Explanation Using Uncertainty Based Class Activation Maps (2019) — 84 citations
• Associations of fats and carbohydrate intake with cardiovascular disease and mortality in 18 countries from five continents (PURE): a prospective cohort study. (2017) — 943 citations