Subramanian Ramamoorthy
Artificial Intelligence · 2011–2019
A researcher in the Science corpus: 6 papers; trusts 166 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 35 citations into it; #11,208 of 35,345 by trust here, #23,077 by citations
- Computer Vision and Pattern Recognition — 35 citations into it; #14,394 of 21,575 by trust here, #14,478 by citations
- Generative Models — 21 citations into it
- Reinforcement Learning — 21 citations into it
- Management Science and Operations Research — 15 citations into it; #3,781 of 11,946 by trust here, #7,638 by citations
- Optimization & Training — 9 citations into it
- Economics and Econometrics — 6 citations into it
- Safety Research — 6 citations into it
Whom Subramanian Ramamoorthy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- J. Urgen Schmidhuber
- Richard S. Sutton
- Michael H. Bowling
- Andrew Barto
- Geoffrey E. Hinton
- Caroline Claus
- Masaki Saito
- Yoshua Bengio
- Alex Krizhevsky
- Yann LeCun
Who trusts Subramanian Ramamoorthy overall
- Stefano V. Albrecht
- Peter Stone
- Filippos Christianos
- Georgios Papoudakis
- Arrasy Rahman
- Oier Mees
- Pablo Hernandez-Leal
Papers from Subramanian Ramamoorthy's perspective
Ordered by how strongly the researchers Subramanian Ramamoorthy 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Lower Dimensional Kernels for Video Discriminators (2019) — 53 citations
- Learning spatial relationships between objects (2011) — 113 citations
- Comparative evaluation of MAL algorithms in a diverse set of ad hoc team problems (2012) — 32 citations
- A game-theoretic model and best-response learning method for ad hoc coordination in multiagent systems (2013) — 134 citations
- The ORCA Hub: Explainable Offshore Robotics through Intelligent Interfaces (2018) — 40 citations
- A Multitask Representation Using Reusable Local Policy Templates (2012) — 10 citations