Seshadri Tirunillai
Sociology and Political Science · 2012–2021
A researcher in the Science corpus: 4 papers; trusts 49 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Sociology and Political Science — 43 citations into it; #5,953 of 22,756 by trust here, #9,254 by citations
- Marketing — 33 citations into it; #1,550 of 6,289 by trust here, #2,815 by citations
- Artificial Intelligence — 14 citations into it
- Management Science and Operations Research — 14 citations into it
- Finance — 13 citations into it; #2,217 of 10,518 by trust here, #3,280 by citations
- Economics and Econometrics — 9 citations into it
- Literature and Literary Theory — 9 citations into it
- Natural Language Processing — 8 citations into it
Whom Seshadri Tirunillai trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David M. Blei
- Xueming Luo
- David John Cameron MacKay
- Thorsten Joachims
- Lars Peter Hansen
- Justin Grimmer
- Daniel B. Nelson
- J. Fleiss
- Helmut Ltkepohl
- Gerard J. Tellis
Who trusts Seshadri Tirunillai overall
- Cait Lamberton
- Abhishek Borah
- Gerard J. Tellis
- Yiyi Li
- Liye Ma
- Guiyang Xiong
- Artem Timoshenko
- Ashish Kumar
- Xueming Luo
- Thomas Dotzel
Papers from Seshadri Tirunillai's perspective
Ordered by how strongly the researchers Seshadri Tirunillai 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)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Mining Marketing Meaning from Online Chatter: Strategic Brand Analysis of Big Data Using Latent Dirichlet Allocation (2014) — 724 citations
- How Technology is Changing Retail (2021) — 368 citations
- What Drives Virality (Sharing) of Online Digital Content? The Critical Role of Information, Emotion, and Brand Prominence (2019) — 447 citations
- Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance (2012) — 630 citations