Anna Shcherbina
Computer Vision and Pattern Recognition · 2016–2021
A researcher in the Science corpus: 4 papers; trusts 62 researchers and is trusted by 29 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 13 citations into it
- Artificial Intelligence — 10 citations into it; #6,454 of 35,345 by trust here, #8,810 by citations
- Safety, Robustness & Interpretability — 7 citations into it; #431 of 2,251 by trust here, #764 by citations
- Biophysics — 6 citations into it
Whom Anna Shcherbina trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Karen Simonyan
- Matthew D. Zeiler
- Sepp Hochreiter
- Evan Shelhamer
- Geoffrey E. Hinton
- Wojciech Samek
- Yoshua Bengio
- J. Urgen Schmidhuber
- Sebastian Bach
- Alex Krizhevsky
Who trusts Anna Shcherbina overall
- Scott M. Lundberg
- Marco Ancona
- Wojciech Samek
- Mukund Sundararajan
- Reza Shokri
- Su-In Lee
- Haidar Khan
- Menaka Narayanan
- André Henriksen
- Grgoire Montavon
Papers from Anna Shcherbina's perspective
Ordered by how strongly the researchers Anna Shcherbina 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Not Just a Black Box: Learning Important Features Through Propagating Activation Differences (2016) — 887 citations
- Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort (2016) — 604 citations
- Genetics of 35 blood and urine biomarkers in the UK Biobank (2021) — 673 citations
- Not Just A Black Box : Interpretable Deep Learning by Propagating Activation Differences (2016)