Stephanie Rosenthal

Computer Vision and Pattern Recognition · 2005–2017

A researcher in the Science corpus: 6 papers; trusts 4 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Stephanie Rosenthal trusts overall

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

  1. Brian Y. Lim
  2. Joydeep Biswas
  3. Manuela M. Veloso
  4. Jesse Thomason
  5. Anind K. Dey
  6. Drew V. McDermott
  7. Todd Kulesza

Who trusts Stephanie Rosenthal overall

  1. Joydeep Biswas
  2. Manuela M. Veloso
  3. Tekin Meriçli
  4. Leilani H. Gilpin
  5. Javier Chiyah-Garcia
  6. Iolanda Leite
  7. Julia Hirschberg

Papers from Stephanie Rosenthal's perspective

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

  1. Intriguing properties of neural networks
  2. ImageNet classification with deep convolutional neural networks
  3. A survey of robot learning from demonstration
  4. Toolkit to support intelligibility in context-aware applications
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Why and why not explanations improve the intelligibility of context-aware intelligent systems
  7. An effective personal mobile robot agent through symbiotic human-robot interaction
  8. Too much, too little, or just right? Ways explanations impact end users' mental models
  9. Adaptive deconvolutional networks for mid and high level feature learning
  10. ImageNet: A large-scale hierarchical image database

Their papers