Chinnadhurai Sankar
Artificial Intelligence · 2015–2019
A researcher in the Science corpus: 7 papers; trusts 72 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 171 citations into it; #32,480 of 35,345 by trust here, #7,241 by citations
- Natural Language Processing — 128 citations into it; #5,233 of 5,688 by trust here, #1,891 by citations
- Reinforcement Learning — 81 citations into it
- Computer Vision and Pattern Recognition — 40 citations into it
- Evaluation & Benchmarks — 23 citations into it
- Model Architectures — 16 citations into it
- Representation & Self-Supervised Learning — 13 citations into it
Whom Chinnadhurai Sankar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard S. Sutton
- Yoshua Bengio
- Ronald J. Williams
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Sepp Hochreiter
- J. Urgen Schmidhuber
- Doina Precup
- Alex Krizhevsky
Who trusts Chinnadhurai Sankar overall
- Myle Ott
- Iulian Serban
- Saku Sugawara
- Thang M. Pham
- Longxuan Ma
- Jinjie Ni
- Abigail See
- Endang Wahyu Pamungkas
- Natasha Jaques
- Emily Dinan
Papers from Chinnadhurai Sankar's perspective
Ordered by how strongly the researchers Chinnadhurai Sankar 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
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset (2019) — 246 citations
- A Deep Reinforcement Learning Chatbot (2017) — 245 citations
- Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study (2019) — 125 citations
- Variance Reduction in SGD by Distributed Importance Sampling (2015) — 227 citations
- The Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach (2018) — 30 citations
- Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning (2019) — 15 citations
- The Octopus Approach to the Alexa Competition : A Deep Ensemble-based Socialbot (2017)