Victor Schmidt

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 9 citations into it
• ML Systems & Hardware — 5 citations into it

Whom Victor Schmidt trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Jimmy Ba
4. Karen Simonyan
5. Anuj Karpatne
6. X. Zhang
7. Geoffrey E. Hinton
8. J. Gao
9. Francesco Dottori
10. Alex Krizhevsky

Who trusts Victor Schmidt overall

1. Aimee van Wynsberghe
2. Alexandra Sasha Luccioni
3. David A. Patterson
4. Anne-Laure Ligozat

Papers from Victor Schmidt's perspective

Ordered by how strongly the researchers Victor Schmidt trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Quantifying the Carbon Emissions of Machine Learning (2019) — 970 citations
• Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks (2019) — 43 citations