Leon Klein

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 42 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 34 citations into it
• Generative Models — 29 citations into it
• Computer Vision and Pattern Recognition — 28 citations into it
• Probabilistic & Bayesian Methods — 23 citations into it
• Statistical and Nonlinear Physics — 21 citations into it; #6,299 of 10,127 by trust here, #6,421 by citations
• Model Architectures — 10 citations into it
• Signal Processing — 9 citations into it
• Molecular Biology — 6 citations into it; #9,651 of 17,773 by trust here, #14,509 by citations

Whom Leon Klein trusts overall

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

1. Diederik P. Kingma
2. Danilo Jimenez Rezende
3. Frank No'e
4. Laurent Dinh
5. Geoffrey E. Hinton
6. Yoshua Bengio
7. Jimmy Ba
8. Alex Krizhevsky
9. Jonas Köhler
10. Michael F. Hutchinson

Who trusts Leon Klein overall

1. Jonas Köhler
2. Hao Wu
3. Minkai Xu
4. George Papamakarios
5. Jason Yim

Papers from Leon Klein's perspective

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

Their papers

• Equivariant Flows: exact likelihood generative learning for symmetric densities (2020) — 351 citations
• Equivariant Flows: sampling configurations for multi-body systems with symmetric energies (2019) — 108 citations