Enrico Bertini
Artificial Intelligence · 2011–2020
A researcher in the Science corpus: 8 papers; trusts 59 researchers and is trusted by 23 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 74 citations into it; #15,626 of 35,345 by trust here, #12,761 by citations
- Computer Vision and Pattern Recognition — 63 citations into it; #5,825 of 21,575 by trust here, #6,737 by citations
- Safety, Robustness & Interpretability — 41 citations into it
- Information Systems — 14 citations into it
- Sociology and Political Science — 13 citations into it
- Computational Theory and Mathematics — 6 citations into it
- Statistical Learning Theory — 6 citations into it
- Management Science and Operations Research — 6 citations into it
Whom Enrico Bertini trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ed H. Chi
- Jock D. Mackinlay
- Wei Peng
- Leland Wilkinson
- Stuart Card
- Jeffrey Heer
- David Martens
- Sheelagh Carpendale
- Josua Krause
- Marco Tulio Ribeiro
Who trusts Enrico Bertini overall
Papers from Enrico Bertini's perspective
Ordered by how strongly the researchers Enrico Bertini 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Learning Multiple Layers of Features from Tiny Images
- Visualizing and Understanding Convolutional Networks
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- ViCE: visual counterfactual explanations for machine learning models (2020) — 108 citations
- Empirical Studies in Information Visualization: Seven Scenarios (2012) — 702 citations
- A Principled Way of Assessing Visualization Literacy (2014) — 306 citations
- RuleMatrix: Visualizing and Understanding Classifiers with Rules (2018) — 243 citations
- A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations (2017) — 100 citations
- Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations (2017) — 74 citations
- INFUSE: Interactive Feature Selection for Predictive Modeling of High Dimensional Data (2014) — 183 citations
- Quality Metrics in High-Dimensional Data Visualization: An Overview and Systematization (2011) — 296 citations