Dushyant Rao

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 7 papers; trusts 282 researchers and is trusted by 55 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 197 citations into it; #9,651 of 35,345 by trust here, #3,204 by citations
• Computer Vision and Pattern Recognition — 155 citations into it; #4,479 of 21,575 by trust here, #3,156 by citations
• Meta & Continual Learning — 75 citations into it; #330 of 1,041 by trust here, #55 by citations
• Representation & Self-Supervised Learning — 67 citations into it; #1,831 of 3,145 by trust here, #1,234 by citations
• Model Architectures — 34 citations into it
• Reinforcement Learning — 30 citations into it
• Generative Models — 24 citations into it
• Computational Mechanics — 9 citations into it

Whom Dushyant Rao trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Yoshua Bengio
5. Kaiming He
6. Yann LeCun
7. Ilya Sutskever
8. Alex Graves
9. Ruslan Salakhutdinov
10. Karen Simonyan

Who trusts Dushyant Rao overall

1. Fei Ye
2. Adrian G. Bors
3. Han-Jia Ye
4. Seyed Iman Mirzadeh
5. Jorge Armando Mendez Mendez
6. Liyuan Wang
7. Matthias De Lange
8. Razvan Pascanu
9. Mehrdad Farajtabar
10. Wei-Lun Chao

Papers from Dushyant Rao's perspective

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

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

Their papers

• Meta-Learning with Latent Embedding Optimization (2018) — 1,522 citations
• Vote3Deep: Fast object detection in 3D point clouds using efficient convolutional neural networks (2016) — 541 citations
• Embracing Change: Continual Learning in Deep Neural Networks. (2020) — 628 citations
• Deep tracking in the wild: End-to-end tracking using recurrent neural networks (2018) — 112 citations
• Continual Unsupervised Representation Learning (2019) — 293 citations
• Task-agnostic Continual Learning with Hybrid Probabilistic Models (2021) — 24 citations
• Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks (2016) — 20 citations