Mark Kurtz
Computer Vision and Pattern Recognition · 2020–2021
A researcher in the Science corpus: 2 papers; trusts 176 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 65 citations into it
- Artificial Intelligence — 53 citations into it
- Efficiency & Compression — 39 citations into it
- Radiology, Nuclear Medicine and Imaging — 7 citations into it
- Model Architectures — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Mark Kurtz trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Song Han
- Yann LeCun
- Diederik P. Kingma
- X. Zhang
- Yoshua Bengio
- Jia Deng
- Ilya Sutskever
Papers from Mark Kurtz's perspective
Ordered by how strongly the researchers Mark Kurtz 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
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images