Meenal Narkhede

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 64 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Computer Vision and Pattern Recognition — 14 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Meenal Narkhede trusts overall

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

1. Yoshua Bengio
2. Kaiming He
3. Geoffrey E. Hinton
4. Yann LeCun
5. Sergey Ioffe
6. Xavier Glorot
7. Marc'Aurelio Ranzato
8. Jaka Demsar
9. Kevin M. Passino
10. Alex Krizhevsky

Papers from Meenal Narkhede's perspective

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

Their papers

• A review on weight initialization strategies for neural networks (2021) — 301 citations