Abhyuday N. Jagannatha
Artificial Intelligence · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 46 researchers and is trusted by 12 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 29 citations into it; #10,249 of 35,345 by trust here, #19,873 by citations
- Natural Language Processing — 14 citations into it
- Reinforcement Learning — 13 citations into it
- Model Architectures — 11 citations into it
- Molecular Biology — 7 citations into it; #2,937 of 17,773 by trust here, #11,818 by citations
- Optimization & Training — 7 citations into it
- Medical & Health AI — 5 citations into it
Whom Abhyuday N. Jagannatha trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- John C. Duchi
- Nitish Srivastava
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Sergey Ioffe
- Tomas Mikolov
- Richard S. Sutton
- John D. Lafferty
Who trusts Abhyuday N. Jagannatha overall
- Yuan Luo
- Irena Spasic
- Thien Huu Nguyen
- Matthew Veres
- Sebastian Gehrmann
- Tharindu Fernando
- Ralph Grishman
- Goran Nenadic
- Medhat A. Moussa
- Macarious Abadeer
Papers from Abhyuday N. Jagannatha's perspective
Ordered by how strongly the researchers Abhyuday N. Jagannatha 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
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)