Reza Zafarani
Information Systems · 2013–2018
A researcher in the Science corpus: 4 papers; trusts 79 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 79 citations into it; #2,579 of 8,771 by trust here, #2,821 by citations
- Artificial Intelligence — 76 citations into it; #16,755 of 35,345 by trust here, #17,776 by citations
- Statistical and Nonlinear Physics — 73 citations into it; #9,217 of 10,127 by trust here, #7,024 by citations
- Sociology and Political Science — 57 citations into it; #8,596 of 22,756 by trust here, #12,387 by citations
- Computer Networks and Communications — 24 citations into it
- Computer Vision and Pattern Recognition — 20 citations into it
- Management Science and Operations Research — 18 citations into it
- Signal Processing — 14 citations into it; #5,328 of 7,572 by trust here, #6,355 by citations
Whom Reza Zafarani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- Jon M. Kleinberg
- Radford M. Neal
- Duncan J. Watts
- B. Liu
- Joseph B. Kruskal
- Boris G. Mirkin
- Huan Liu
- Zhiwei Jin
- Réka Albert
Who trusts Reza Zafarani overall
- Ashwin Rajadesingan
- Yutao Zhang
- Jiliang Tang
- Huan Liu
- Hui-Ju Hung
- Charu C. Aggarwal
- Rohit Kumar Kaliyar
- David Bamman
- Xinyi Zhou
- Jie Tang
Papers from Reza Zafarani's perspective
Ordered by how strongly the researchers Reza Zafarani trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Sarcasm Detection on Twitter: A Behavioral Modeling Approach (2015) — 429 citations
- Connecting users across social media sites: a behavioral-modeling approach (2013) — 439 citations
- Fake News: A Survey of Research, Detection Methods, and Opportunities (2018) — 314 citations
- Social Media Mining: An Introduction (2014) — 632 citations