Marie Szafranski
Artificial Intelligence · 2007–2016
A researcher in the Science corpus: 4 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 19 citations into it
- Statistical Learning Theory — 19 citations into it
- Molecular Biology — 11 citations into it
- Statistics and Probability — 8 citations into it
- Representation & Self-Supervised Learning — 7 citations into it
- Computer Vision and Pattern Recognition — 6 citations into it
- Control and Systems Engineering — 5 citations into it
Whom Marie Szafranski trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David A. McAllester
- Corinna Cortes
- Mehryar Mohri
- Michael R. Osborne
- Bin Yu
- Ioannis Tsochantaridis
- Mikhail Belkin
- Asa Ben-Hur
- B. Taskar
- Yoshihiro Yamanishi
Who trusts Marie Szafranski overall
Papers from Marie Szafranski's perspective
Ordered by how strongly the researchers Marie Szafranski 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)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Input Output Kernel Regression (2016)
- Semi-supervised Penalized Output Kernel Regression for Link Prediction (2011) — 74 citations
- Chromatic PAC-Bayes Bounds for Non-IID Data (2009) — 76 citations
- Hierarchical Penalization (2007) — 37 citations