Manish Gupta

Artificial Intelligence · IEEE Transactions on Knowledge and Data Engineering · 2011–2016

A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Statistical and Nonlinear Physics — 17 citations into it
• Natural Language Processing — 16 citations into it
• Signal Processing — 15 citations into it
• Computer Networks and Communications — 12 citations into it; #4,119 of 9,886 by trust here, #6,498 by citations
• Information Systems — 8 citations into it; #3,437 of 8,771 by trust here, #4,188 by citations
• Economics and Econometrics — 6 citations into it

Whom Manish Gupta trusts overall

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

1. Eamonn J. Keogh
2. Kenji Yamanishi
3. Stephanie Forrest
4. Jessica Lin
5. Nong Ye
6. Jiawei Han
7. Stefano Lonardi
8. Michael Mathioudakis
9. Jeff Pasternack
10. Yunyue Zhu

Who trusts Manish Gupta overall

1. Zhiwei Jin
2. Xinyi Zhou
3. Juan Cao
4. Ting-Rui Chiang
5. Subhro Roy
6. Yongdong Zhang
7. Yixuan Cao
8. Oishik Chatterjee
9. Wenchao Yu
10. Dan Roth

Papers from Manish Gupta's perspective

Ordered by how strongly the researchers Manish Gupta 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. ImageNet: A large-scale hierarchical image database
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Equation Parsing : Mapping Sentences to Grounded Equations (2016) — 49 citations
• Evaluating Event Credibility on Twitter (2012) — 298 citations
• Outlier Detection for Temporal Data: A Survey (2014) — 1,031 citations
• Co-author Relationship Prediction in Heterogeneous Bibliographic Networks (2011) — 462 citations