Olga Slizovskaia

Computer Vision and Pattern Recognition · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 20 citations into it
• Artificial Intelligence — 15 citations into it
• Safety, Robustness & Interpretability — 8 citations into it

Whom Olga Slizovskaia trusts overall

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

1. Diederik P. Kingma
2. Dan Hendrycks
3. Jerome H. Friedman
4. David John Cameron MacKay
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Sergey Ioffe
8. Yoshua Bengio

Papers from Olga Slizovskaia's perspective

Ordered by how strongly the researchers Olga Slizovskaia 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Input complexity and out-of-distribution detection with likelihood-based generative models (2019) — 315 citations
• Acoustic Scene Classification by Ensembling Gradient Boosting Machine and Convolutional Neural Networks (2017) — 29 citations