Minghao Gu

Probabilistic & Bayesian Methods · 2019

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 17 citations into it; #1,310 of 1,525 by trust here, #1,515 by citations
• Artificial Intelligence — 14 citations into it; #27,906 of 35,345 by trust here, #34,943 by citations
• Statistics and Probability — 9 citations into it; #10,314 of 12,932 by trust here, #12,603 by citations
• Computer Vision and Pattern Recognition — 6 citations into it
• Generative Models — 6 citations into it

Whom Minghao Gu trusts overall

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

1. David Freedman
2. Danilo Jimenez Rezende
3. Gareth O. Roberts
4. David M. Blei
5. Jiaming Song
6. Radford M. Neal
7. Shakir Mohamed
8. Diederik P. Kingma
9. Steve P. Brooks
10. Nilesh Tripuraneni

Who trusts Minghao Gu overall

1. Hao Wu
2. Jonas Köhler

Papers from Minghao Gu's perspective

Ordered by how strongly the researchers Minghao Gu 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. Gradient-based learning applied to document recognition
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

• Dynamical Sampling with Langevin Normalization Flows (2019) — 5 citations