Hossein Soleimani

Artificial Intelligence · 2017

A researcher in the Science corpus: 2 papers; trusts 28 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 22 citations into it; #21,088 of 35,345 by trust here, #27,551 by citations
• Statistics and Probability — 18 citations into it; #10,512 of 12,932 by trust here, #11,487 by citations
• Probabilistic & Bayesian Methods — 11 citations into it; #1,329 of 1,525 by trust here, #1,365 by citations
• Causal Inference & Discovery — 7 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Management Science and Operations Research — 6 citations into it; #9,291 of 11,946 by trust here, #9,383 by citations
• Medical & Health AI — 5 citations into it

Whom Hossein Soleimani trusts overall

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

1. Dimitris Rizopoulos
2. James Hensman
3. Donald B. Rubin
4. James M. Robins
5. Diederik P. Kingma
6. Zachary Chase Lipton
7. Peter F. Schulam
8. Jennifer L. Hill
9. Lyle Ungar
10. Neil D. Lawrence

Who trusts Hossein Soleimani overall

1. Ioana Bica
2. Lukás Neumann
3. Edward De Brouwer
4. Ahmed M. Alaa
5. Andrew Zisserman
6. Mihaela van der Schaar
7. Jaak Simm
8. Bryan Lim

Papers from Hossein Soleimani's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Learning Multiple Layers of Features from Tiny Images
8. ImageNet: A large-scale hierarchical image database
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction (2017) — 60 citations
• Learning Treatment-Response Models from Multivariate Longitudinal Data (2017) — 21 citations