Igor T. Podolak

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 T. Podolak trusts overall

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

1. Tom White
2. Sergey Ioffe
3. Alec Radford

Papers from Igor T. Podolak's perspective

Ordered by how strongly the researchers Igor T. Podolak 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. GENERATIVE ADVERSARIAL NETS
3. ImageNet classification with deep convolutional neural networks
4. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Understanding the difficulty of training deep feedforward neural networks
7. Gradient-based learning applied to document recognition
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Deep Learning Face Attributes in the Wild
10. ImageNet: A large-scale hierarchical image database

Their papers

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