Darshan Patil

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 97 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 94 citations into it
• Computer Vision and Pattern Recognition — 53 citations into it
• Representation & Self-Supervised Learning — 30 citations into it
• Natural Language Processing — 21 citations into it
• Optimization & Training — 20 citations into it
• Reinforcement Learning — 5 citations into it

Whom Darshan Patil trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Yann LeCun
6. Diederik P. Kingma
7. Ilya Sutskever
8. Ross B. Girshick
9. Tomas Mikolov
10. Richard Socher

Who trusts Darshan Patil overall

1. Liyuan Wang

Papers from Darshan Patil's perspective

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

Their papers

• An Empirical Investigation of the Role of Pre-training in Lifelong Learning (2021) — 180 citations
• Towards modular and programmable architecture search (2019) — 31 citations