Maharshi Gor
Artificial Intelligence · 2021
A researcher in the Science corpus: 2 papers; trusts 45 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 46 citations into it
- Natural Language Processing — 32 citations into it
- Computer Vision and Pattern Recognition — 27 citations into it
- Evaluation & Benchmarks — 12 citations into it
- Model Architectures — 9 citations into it
- Information Retrieval & Search — 7 citations into it
Whom Maharshi Gor trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kenton C. T. Lee
- Geoffrey E. Hinton
- Yoshua Bengio
- Jordan L. Boyd-Graber
- Diederik P. Kingma
- Percy Liang
- Ming-Wei Chang
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
Who trusts Maharshi Gor overall
Papers from Maharshi Gor's perspective
Ordered by how strongly the researchers Maharshi Gor trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy (2021) — 11 citations
- MATE: Multi-view Attention for Table Transformer Efficiency (2021) — 108 citations