Jay Mohta

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it

Whom Jay Mohta trusts overall

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

1. Geoffrey E. Hinton
2. Noam Shazeer
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Alex Krizhevsky
7. Yann LeCun
8. Kaiming He
9. Jacob Devlin
10. Alex Graves

Papers from Jay Mohta's perspective

Ordered by how strongly the researchers Jay Mohta trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Language Models are Few-Shot Learners (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)

Their papers

• Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning (2022) — 1,382 citations