Aashish Jain

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Natural Language Processing — 9 citations into it
• Evaluation & Benchmarks — 6 citations into it
• Multimodal Learning — 6 citations into it

Whom Aashish Jain trusts overall

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

1. Kaiming He
2. Jia Deng
3. Geoffrey E. Hinton
4. Michael J. Denkowski
5. Alec Radford
6. Yoshua Bengio
7. Ilya Sutskever
8. Alex Krizhevsky
9. Diederik P. Kingma
10. X. Zhang

Papers from Aashish Jain's perspective

Ordered by how strongly the researchers Aashish Jain 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. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens (2019) — 434 citations
• Multimodal Conditionality for Natural Language Generation (2021) — 10 citations