Eytan Bakshy
Statistical and Nonlinear Physics · 2008–2020
A researcher in the Science corpus: 11 papers; trusts 83 researchers and is trusted by 30 researchers here, as inferred from the citation graph.
Subfields
- Statistical and Nonlinear Physics — 71 citations into it; #2,305 of 10,127 by trust here, #548 by citations
- Artificial Intelligence — 70 citations into it; #23,208 of 35,345 by trust here, #22,463 by citations
- Management Science and Operations Research — 48 citations into it; #7,279 of 11,946 by trust here, #5,787 by citations
- Sociology and Political Science — 48 citations into it; #2,316 of 22,756 by trust here, #600 by citations
- Communication — 40 citations into it; #672 of 3,460 by trust here, #171 by citations
- Computational Theory and Mathematics — 37 citations into it; #8,512 of 12,182 by trust here, #7,142 by citations
- Statistics and Probability — 28 citations into it
- Computer Vision and Pattern Recognition — 23 citations into it
Whom Eytan Bakshy trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Duncan J. Watts
- Leo Breiman
- Niko Speybroeck
- Sinan Aral
- Charles F. Manski
- Guido W. Imbens
- Lars Backstrom
- Donald R. Jones
- Lada A. Adamic
- Jon M. Kleinberg
Who trusts Eytan Bakshy overall
- Ravi Bapna
- Iyad Rahwan
- Amit Sharma
- Sharad Goel
- Rediet Abebe
- J. P. Gleeson
- Dean Eckles
- Dimitar Nikolov
- E. Peterson
- Adam Badawy
Papers from Eytan Bakshy's perspective
Ordered by how strongly the researchers Eytan Bakshy 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
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Auto-Encoding Variational Bayes (International Conference on Learning Representations)
- Et al
Their papers
- Constrained Bayesian Optimization with Noisy Experiments (2017) — 348 citations
- Everyone's an influencer: quantifying influence on twitter (2011) — 1,971 citations
- Exposure to ideologically diverse news and opinion on Facebook (2015) — 2,992 citations
- The role of social networks in information diffusion (2012) — 1,651 citations
- Quantifying the invisible audience in social networks (2013) — 385 citations
- Social influence in social advertising: evidence from field experiments (2012) — 291 citations
- Center of Attention: How Facebook Users Allocate Attention across Friends (2011) — 96 citations
- Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization (2020) — 381 citations
- Estimating peer effects in networks with peer encouragement designs (2016) — 134 citations
- BoTorch: Programmable Bayesian Optimization in PyTorch (2019) — 102 citations
- Knowledge sharing and yahoo answers: everyone knows something (2008) — 854 citations