Justin Engelmann

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 55 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Generative Models — 16 citations into it
• Statistics and Probability — 6 citations into it
• Accounting — 5 citations into it

Whom Justin Engelmann trusts overall

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

1. Ian J. Goodfellow
2. Diederik P. Kingma
3. Jaka Demsar
4. Klaus Nordhausen
5. Kaiming He
6. Individualized Treat
7. Haibo He
8. Yoshua Bengio
9. Geoffrey E. Hinton
10. Jimmy Ba

Who trusts Justin Engelmann overall

1. Zilong Zhao
2. Aditya Kunar

Papers from Justin Engelmann's perspective

Ordered by how strongly the researchers Justin Engelmann 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning (2020) — 315 citations