Viraj Kulkarni

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Federated & Distributed Learning — 12 citations into it
• Meta & Continual Learning — 6 citations into it
• Optimization & Training — 6 citations into it

Whom Viraj Kulkarni trusts overall

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

1. H. Brendan McMahan
2. Chelsea Finn
3. Alex Nichol
4. Geoffrey E. Hinton
5. Alireza Fallah
6. Yishay Mansour
7. Yihan Jiang
8. Pieter Abbeel
9. Kangkang Wang
10. Sergey Levine

Who trusts Viraj Kulkarni overall

1. Yutao Huang
2. Lingyang Chu

Papers from Viraj Kulkarni's perspective

Ordered by how strongly the researchers Viraj Kulkarni trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Survey of Personalization Techniques for Federated Learning (2020) — 394 citations