Oliver Dürr

Probabilistic & Bayesian Methods · 2022

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 15 citations into it
• Artificial Intelligence — 14 citations into it
• Generative Models — 6 citations into it

Whom Oliver Dürr trusts overall

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

1. Danilo Jimenez Rezende
2. Charles Blundell
3. Laurent Dinh
4. Rajesh Ranganath
5. George Papamakarios
6. Diederik P. Kingma
7. Balaji Lakshminarayanan
8. Ivan Kobyzev
9. Geoffrey E. Hinton
10. Shakir Mohamed

Papers from Oliver Dürr's perspective

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

Their papers

• Bernstein flows for flexible posteriors in variational Bayes (2022) — 4 citations