Gabriel Schwartz

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 3 papers; trusts 181 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 96 citations into it
• Computer Graphics and Computer-Aided Design — 41 citations into it
• Computational Mechanics — 38 citations into it
• 3D Vision & Pose — 27 citations into it
• Aerospace Engineering — 15 citations into it
• Artificial Intelligence — 13 citations into it
• Optimization & Training — 7 citations into it
• Geology — 6 citations into it

Whom Gabriel Schwartz trusts overall

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

1. Diederik P. Kingma
2. Johannes L. Schönberger
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Yoshua Bengio
7. Jimmy Ba
8. Yann LeCun
9. Karen Simonyan
10. Ross B. Girshick

Papers from Gabriel Schwartz's perspective

Ordered by how strongly the researchers Gabriel Schwartz 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Going deeper with convolutions
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. Long Short-Term Memory
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Mixture of volumetric primitives for efficient neural rendering (2021) — 370 citations
• Neural volumes (2019) — 338 citations
• Theano: A Python framework for fast computation of mathematical expressions (2016) — 2,380 citations