V. Sreekanth Annapureddy

Artificial Intelligence · 2008–2015

A researcher in the Science corpus: 2 papers; trusts 48 researchers and is trusted by 22 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it; #6,340 of 21,575 by trust here, #7,852 by citations
• Efficiency & Compression — 10 citations into it; #334 of 1,264 by trust here, #613 by citations
• Electrical and Electronic Engineering — 8 citations into it
• Model Architectures — 6 citations into it; #723 of 2,278 by trust here, #1,092 by citations

Whom V. Sreekanth Annapureddy trusts overall

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

1. Tie Liu
2. Kaiming He
3. Geoffrey E. Hinton
4. Pramod Viswanath
5. Sergey Ioffe
6. Yoshua Bengio
7. Igal Sason
8. Alex Krizhevsky
9. Christian Szegedy
10. Raúl Hernán Etkin

Who trusts V. Sreekanth Annapureddy overall

1. Georgios Georgiadis
2. Jeff Johnson
3. Raj Dabre
4. Viveck R. Cadambe
5. Yury Nahshan
6. Darryl Dexu Lin
7. Ruizhou Ding
8. Liang Liu
9. Arash Asadi

Papers from V. Sreekanth Annapureddy's perspective

Ordered by how strongly the researchers V. Sreekanth Annapureddy 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. Going deeper with convolutions
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Fixed Point Quantization of Deep Convolutional Networks (2015) — 864 citations
• Gaussian Interference Networks: Sum Capacity in the Low-Interference Regime and New Outer Bounds on the Capacity Region (2008) — 464 citations