Grant Robert Schoenebeck

Artificial Intelligence · 2009–2018

A researcher in the Science corpus: 3 papers; trusts 27 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it; #22,923 of 35,345 by trust here, #8,706 by citations
• Safety, Robustness & Interpretability — 26 citations into it
• Statistical and Nonlinear Physics — 16 citations into it; #8,195 of 10,127 by trust here, #9,682 by citations
• Computer Vision and Pattern Recognition — 10 citations into it
• Algorithms & Complexity — 5 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Grant Robert Schoenebeck trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Mark Newman
2. Duncan J. Watts
3. Jon M. Kleinberg
4. Jure Leskovec
5. Mark S. Handcock
6. Remco van der Hofstad
7. Krista Gile
8. Mark S. Granovetter
9. Peter Sheridan Dodds
10. Damon Centola

Who trusts Grant Robert Schoenebeck overall

1. Momin M. Malik
2. Gang Wang
3. Carlos Castillo
4. Alexandra Olteanu
5. Umashanthi Pavalanathan

Papers from Grant Robert Schoenebeck's perspective

Ordered by how strongly the researchers Grant Robert Schoenebeck trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Learning Multiple Layers of Features from Tiny Images
4. Collective dynamics of ‘small-world’ networks
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Intriguing properties of neural networks
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality (2018) — 849 citations
• Potential networks, contagious communities, and understanding social network structure (2013) — 22 citations
• Detecting Spam in a Twitter Network (2009) — 385 citations