Ajinkya Kulkarni

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Generative Models — 5 citations into it

Whom Ajinkya Kulkarni trusts overall

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

1. Kihyuk Sohn
2. Mahmut Kaya
3. Ryan J. Prenger
4. Robert C. Streijl
5. Yuxuan Wang
6. Ya-Jie Zhang
7. Samuel R. Bowman
8. Vatsal Aggarwal
9. Geoffrey E. Hinton
10. Jonathan Shen

Papers from Ajinkya Kulkarni's perspective

Ordered by how strongly the researchers Ajinkya 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Improving transfer of expressivity for end-to-end multispeaker text-to-speech synthesis (2021) — 15 citations