Daniel M. Spokoyny

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 39 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Generative Models — 16 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Daniel M. Spokoyny trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Ruslan Salakhutdinov
4. Kaiming He
5. Yoshua Bengio
6. Sepp Hochreiter
7. David M. Blei
8. Alex Krizhevsky
9. Max Welling
10. Radford M. Neal

Who trusts Daniel M. Spokoyny overall

1. Chunyuan Li
2. John Wieting
3. Yi Ren
4. Peng Xu
5. Bryan Lim

Papers from Daniel M. Spokoyny's perspective

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

Their papers

• Lagging Inference Networks and Posterior Collapse in Variational Autoencoders (2019) — 307 citations