Sitaram Asur
Statistical and Nonlinear Physics · 2007–2012
A researcher in the Science corpus: 5 papers; trusts 30 researchers and is trusted by 62 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 50 citations into it; #3,443 of 10,127 by trust here, #3,616 by citations
- Artificial Intelligence — 20 citations into it
- Sociology and Political Science — 15 citations into it; #8,248 of 22,756 by trust here, #14,364 by citations
- Management Science and Operations Research — 10 citations into it
- Information Systems — 9 citations into it; #6,595 of 8,771 by trust here, #7,386 by citations
- Communication — 6 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
- Network Science & Complex Systems — 5 citations into it
Whom Sitaram Asur trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Newman
- Jon M. Kleinberg
- Jure Leskovec
- Bo Pang
- Dekang Lin
- Bernardo A. Huberman
- David Kempe
- David Liben-Nowell
- Alexander Strehl
- Evgeniy Gabrilovich
Who trusts Sitaram Asur overall
- Emre Kıcıman
- Eszter Hargittai
- Dimitris J. Bertsimas
- Anastasia Giahanou
- Adam Bermingham
- Sanghee Oh
- Jaehyuk Park
- Yoav Artzi
- Matthew S. Gerber
- Jianqing Fan
Papers from Sitaram Asur's perspective
Ordered by how strongly the researchers Sitaram Asur 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)
- Authoritative sources in a hyperlinked environment
- The Anatomy of a Large-Scale Hypertextual Web Search Engine
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Going deeper with convolutions
Their papers
- Predicting the Future with Social Media (2010) — 2,354 citations
- An event-based framework for characterizing the evolutionary behavior of interaction graphs (2007) — 435 citations
- The Pulse of News in Social Media: Forecasting Popularity (2012) — 453 citations
- Trends in Social Media: Persistence and Decay (2011) — 408 citations
- Influence and passivity in social media (2010) — 761 citations