Vivek Datla

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 79 citations into it
• Natural Language Processing — 50 citations into it
• Computer Vision and Pattern Recognition — 37 citations into it
• Model Architectures — 16 citations into it
• Medical & Health AI — 14 citations into it
• Reinforcement Learning — 13 citations into it
• Molecular Biology — 10 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Vivek Datla trusts overall

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

1. Diederik P. Kingma
2. Richard S. Sutton
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Richard Bellman
6. Alex Krizhevsky
7. Ilya Sutskever
8. Edward Choi
9. Alex Graves
10. Jimmy Ba

Who trusts Vivek Datla overall

1. Chao Yu

Papers from Vivek Datla's perspective

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

Their papers

• DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference (2018) — 105 citations
• Condensed Memory Networks for Clinical Diagnostic Inferencing (2016) — 108 citations
• VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019 (2019) — 322 citations
• Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning (2017) — 29 citations
• Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study (2017) — 43 citations