Gaurav Kumar Nayak
Computer Vision and Pattern Recognition · 2019–2020
A researcher in the Science corpus: 2 papers; trusts 68 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 25 citations into it
- Artificial Intelligence — 22 citations into it; #34,115 of 35,345 by trust here, #18,186 by citations
- Efficiency & Compression — 7 citations into it; #1,221 of 1,264 by trust here, #925 by citations
- Evaluation & Benchmarks — 5 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
- Signal Processing — 5 citations into it
Whom Gaurav Kumar Nayak trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- Ilya Sutskever
- Yoshua Bengio
- Kaiming He
- Oriol Vinyals
- Christian Szegedy
- Diederik P. Kingma
- L. Eon Bottou
Who trusts Gaurav Kumar Nayak overall
- Jianping Gou
- Paul Micaelli
- Yuang Liu
- Bo Zhao
- Konda Reddy Mopuri
- Mozhgan Pourkeshavarz
- Vinay Kumar Verma
- Matan Haroush
- Akshay Chawla
- Liangchen Luo
Papers from Gaurav Kumar Nayak's perspective
Ordered by how strongly the researchers Gaurav Kumar Nayak 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
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Zero-Shot Knowledge Distillation in Deep Networks (2019) — 267 citations
- Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation (2020) — 22 citations