Zachary C. Steinert-Threlkeld
Sociology and Political Science · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 105 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Sociology and Political Science — 38 citations into it; #11,706 of 22,756 by trust here, #16,952 by citations
- Artificial Intelligence — 30 citations into it; #22,695 of 35,345 by trust here, #32,362 by citations
- Statistical and Nonlinear Physics — 27 citations into it; #3,535 of 10,127 by trust here, #9,324 by citations
- Communication — 23 citations into it; #961 of 3,460 by trust here, #3,220 by citations
- Computer Vision and Pattern Recognition — 19 citations into it; #13,770 of 21,575 by trust here, #18,266 by citations
- Information Systems — 11 citations into it
- General Social Sciences — 6 citations into it; #95 of 274 by trust here, #202 by citations
- Signal Processing — 6 citations into it
Whom Zachary C. Steinert-Threlkeld trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Clayton A. Davis
- Margaret E. Roberts
- Kaiming He
- Brandon M Stewart
- Zeynep Tufekci
- Bruno Gonçalves
- Sandra González-Bailón
- Onur Varol
- Justin Grimmer
- Diederik P. Kingma
Who trusts Zachary C. Steinert-Threlkeld overall
Papers from Zachary C. Steinert-Threlkeld's perspective
Ordered by how strongly the researchers Zachary C. Steinert-Threlkeld trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Protest Activity Detection and Perceived Violence Estimation from Social Media Images (2017) — 104 citations
- Understanding the Political Ideology of Legislators from Social Media Images (2019) — 54 citations
- Twitter as Data (2018) — 116 citations