Ilmun Kim

Statistics and Probability · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 45 citations into it
• Artificial Intelligence — 20 citations into it
• Statistical Learning Theory — 9 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Finance — 5 citations into it

Whom Ilmun Kim trusts overall

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

1. Arthur Gretton
2. Joseph P. Romano
3. G'abor J. Sz'ekely
4. Ludwig Baringhaus
5. W. Hoeffding
6. Sivaraman Balakrishnan
7. E. Chung
8. Paul R. Rosenbaum
9. Liam Paninski
10. Arnold J. Stromberg

Papers from Ilmun Kim's perspective

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

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

Their papers

• Robust multivariate nonparametric tests via projection averaging (2018) — 75 citations
• Minimax optimality of permutation tests (2020) — 68 citations