Aishwarya Agarwal

Artificial Intelligence · 2022

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 — 31 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Meta & Continual Learning — 14 citations into it
• Representation & Self-Supervised Learning — 14 citations into it

Whom Aishwarya Agarwal trusts overall

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

1. Alex Krizhevsky
2. Diederik P. Kingma
3. Kaiming He
4. Geoffrey E. Hinton
5. Ilya Sutskever
6. Yoshua Bengio
7. Oriol Vinyals
8. Tomas Mikolov
9. Yann LeCun
10. Karen Simonyan

Papers from Aishwarya Agarwal's perspective

Ordered by how strongly the researchers Aishwarya Agarwal 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Learning Multiple Layers of Features from Tiny Images
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Semantics-Driven Generative Replay for Few-Shot Class Incremental Learning (2022) — 42 citations