Chaitanya P. Shivade

Artificial Intelligence · 2013–2018

A researcher in the Science corpus: 2 papers; trusts 71 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it; #18,074 of 35,345 by trust here, #18,186 by citations
• Natural Language Processing — 23 citations into it
• Molecular Biology — 18 citations into it; #6,659 of 17,773 by trust here, #15,203 by citations
• Evaluation & Benchmarks — 11 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Chaitanya P. Shivade trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Kyunghyun Cho
4. Geoffrey E. Hinton
5. Dzmitry Bahdanau
6. Dekang Lin
7. Richard Socher
8. Ilya Sutskever
9. Oriol Vinyals
10. Samuel R. Bowman

Who trusts Chaitanya P. Shivade overall

1. Christopher Kotfila
2. Yifan Peng
3. Zexian Zeng
4. Yasuhide Miura
5. Hicham El Boukkouri
6. Ozlem Uzuner

Papers from Chaitanya P. Shivade's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Lessons from Natural Language Inference in the Clinical Domain (2018) — 329 citations
• A review of approaches to identifying patient phenotype cohorts using electronic health records (2013) — 528 citations