Tejaswini Pedapati
Artificial Intelligence · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 494 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 106 citations into it; #27,206 of 35,345 by trust here, #25,040 by citations
- Computer Vision and Pattern Recognition — 104 citations into it; #16,712 of 21,575 by trust here, #13,815 by citations
- Neural Architecture Search & AutoML — 40 citations into it; #216 of 283 by trust here, #250 by citations
- Model Architectures — 32 citations into it
- Optimization & Training — 23 citations into it
- Efficiency & Compression — 18 citations into it
- Reinforcement Learning — 14 citations into it
- Computational Theory and Mathematics — 10 citations into it
Whom Tejaswini Pedapati trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Barret Zoph
- Yoshua Bengio
- Kaiming He
- Karen Simonyan
- Quoc V. Le
- Yann LeCun
- Diederik P. Kingma
- Ilya Sutskever
Who trusts Tejaswini Pedapati overall
Papers from Tejaswini Pedapati's perspective
Ordered by how strongly the researchers Tejaswini Pedapati 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
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Understanding Unequal Gender Classification Accuracy from Face Images (2018) — 53 citations
- Inductive Transfer for Neural Architecture Optimization (2019) — 9 citations
- A Survey on Neural Architecture Search (2019) — 293 citations