Igor Sieradzki

Generative Models · 2018

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Generative Models — 5 citations into it

Whom Igor Sieradzki trusts overall

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

1. Tom White
2. Sergey Ioffe
3. Alec Radford
4. Georgios Arvanitidis
5. Yannic Kilcher
6. Christian Szegedy
7. Ziwei Liu
8. Yoshua Bengio
9. Xavier Glorot

Papers from Igor Sieradzki's perspective

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

1. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
2. ImageNet classification with deep convolutional neural networks
3. GENERATIVE ADVERSARIAL NETS
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
9. Attention is All you Need (Neural Information Processing Systems)
10. Long Short-Term Memory

Their papers

• Distribution-Interpolation Trade off in Generative Models (2018) — 24 citations