Robinder G. Khemani
Artificial Intelligence · 2009–2016
A researcher in the Science corpus: 5 papers; trusts 32 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 47 citations into it; #17,397 of 35,345 by trust here, #12,083 by citations
- Computer Vision and Pattern Recognition — 15 citations into it
- Model Architectures — 15 citations into it
- Signal Processing — 13 citations into it; #3,536 of 7,572 by trust here, #1,669 by citations
- Molecular Biology — 11 citations into it
- Statistics and Probability — 11 citations into it; #6,336 of 12,932 by trust here, #4,964 by citations
- Natural Language Processing — 8 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
Whom Robinder G. Khemani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jerome H. Friedman
- Geoffrey E. Hinton
- Yoshua Bengio
- Pascal Vincent
- Diederik P. Kingma
- Alex Krizhevsky
- Sepp Hochreiter
- Ilya Sutskever
- Jimmy Ba
- J. Ross Quinlan
Who trusts Robinder G. Khemani overall
- Zachary Chase Lipton
- Zhengping Che
- David C. Kale
- Alfredo Vellido
- Yinchong Yang
- Sarah Tan
- Sanjay Purushotham
- Marzyeh Ghassemi
- Javad Azizi
- Randall C. Wetzel
Papers from Robinder G. Khemani's perspective
Ordered by how strongly the researchers Robinder G. Khemani trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Unsupervised pattern discovery in electronic health care data using probabilistic clustering models (2012) — 186 citations
- Interpretable Deep Models for ICU Outcome Prediction (2016) — 293 citations
- Distilling Knowledge from Deep Networks with Applications to Healthcare Domain (2015) — 147 citations
- Pediatric Acute Respiratory Distress Syndrome: Consensus Recommendations From the Pediatric Acute Lung Injury Consensus Conference (2015) — 727 citations
- Effect of tidal volume in children with acute hypoxemic respiratory failure (2009) — 159 citations