Ravi Shroff
Statistics and Probability · 2016–2020
A researcher in the Science corpus: 7 papers; trusts 29 researchers and is trusted by 18 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 38 citations into it
- Artificial Intelligence — 18 citations into it; #26,779 of 35,345 by trust here, #16,166 by citations
- Safety, Robustness & Interpretability — 16 citations into it
- AI Ethics, Fairness & Society — 12 citations into it; #84 of 494 by trust here, #144 by citations
- Economics and Econometrics — 8 citations into it
- Information Systems — 8 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
- Computer Vision and Pattern Recognition — 5 citations into it
Whom Ravi Shroff trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alekh Agarwal
- Berk Ustun
- Cynthia Rudin
- Miroslav Dud'ik
- Himabindu Lakkaraju
- Jennifer L. Hill
- Gerd Gigerenzer
- Olivier Chapelle
- Paul R. Rosenbaum
- Donald B. Rubin
Who trusts Ravi Shroff overall
- Berk Ustun
- Sam Corbett-Davies
- Sharad Goel
- Susan Athey
- Muhammad Bilal Zafar
- Alexandra Chouldechova
- Emma Pierson
- Camelia Simoiu
- Nathan Kallus
- Sarah Tan
Papers from Ravi Shroff's perspective
Ordered by how strongly the researchers Ravi Shroff 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)
- Gradient-based learning applied to document recognition
- Regression Shrinkage and Selection via the Lasso
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Predictive Analytics for City Agencies: Lessons from Children's Services (2017) — 29 citations
- Precinct or Prejudice? Understanding Racial Disparities in New York City's Stop-and-Frisk Policy (2016) — 252 citations
- Simple Rules for Complex Decisions (2017) — 107 citations
- A large-scale analysis of racial disparities in police stops across the United States (2020) — 449 citations
- Personalized risk assessments in the criminal justice system (2016) — 23 citations
- Simple rules to guide expert classifications (2020) — 44 citations
- The Measure and Mismeasure of Fairness (2018) — 229 citations