V. Gandikota
Artificial Intelligence · 2022
A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 24 citations into it; #34,055 of 35,345 by trust here, #26,682 by citations
- Optimization & Training — 15 citations into it; #2,535 of 2,601 by trust here, #2,162 by citations
- Computational Mechanics — 7 citations into it; #9,568 of 10,001 by trust here, #6,877 by citations
- Computer Vision and Pattern Recognition — 6 citations into it
- Computer Networks and Communications — 5 citations into it
Whom V. Gandikota trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Chih-Jen Lin
- Nikko Ström
- Dan Alistarh
- Sebastian U. Stich
- Reza Shokri
- Ananda Theertha Suresh
- Ú. Erlingsson
- Shai Shalev-Shwartz
- Stelios D. Georgiou
Who trusts V. Gandikota overall
- Wei-Ning Chen
- Yuqing Du
- Peter Kairouz
- Antonious M. Girgis
- Prathamesh Mayekar
- Ayfer Özgür
- Deepesh Data
Papers from V. Gandikota's perspective
Ordered by how strongly the researchers V. Gandikota trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Learning Multiple Layers of Features from Tiny Images
- 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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- vqSGD: Vector Quantized Stochastic Gradient Descent (2022) — 136 citations