Anubhav Ashok
Artificial Intelligence · 2017
A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 20 citations into it; #22,974 of 35,345 by trust here, #20,377 by citations
- Computer Vision and Pattern Recognition — 14 citations into it; #14,202 of 21,575 by trust here, #13,542 by citations
- Efficiency & Compression — 13 citations into it; #804 of 1,264 by trust here, #987 by citations
- Model Architectures — 9 citations into it
- Optimization & Training — 5 citations into it
Whom Anubhav Ashok trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- Alex Krizhevsky
- Ronald J. Williams
- Geoffrey E. Hinton
- Jimmy Ba
- Barret Zoph
- Yoshua Bengio
- Song Han
- Karen Simonyan
- Ilya Sutskever
Who trusts Anubhav Ashok overall
- Han Cai
- Lin Wang
- Yihui He
- Minsoo Kang
- Shengcao Cao
- Jianping Gou
- Song Han
- Hanyang Kong
- Kuk-Jin Yoon
- Chuang Gan
Papers from Anubhav Ashok's perspective
Ordered by how strongly the researchers Anubhav Ashok 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
Their papers
- N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning (2017) — 182 citations