Liuyi Yao
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 — 77 citations into it
- Causal Inference & Discovery — 43 citations into it
- Artificial Intelligence — 39 citations into it
- Probabilistic & Bayesian Methods — 14 citations into it
- Management Science and Operations Research — 11 citations into it
- Reinforcement Learning — 9 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
- Evaluation & Benchmarks — 5 citations into it
Whom Liuyi Yao trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Donald B. Rubin
- James M. Robins
- Judea Pearl
- Jennifer L. Hill
- Susan A. Murphy
- Uri Shalit
- Paul R. Rosenbaum
- Stefan Wager
- Leo Breiman
- Susan Athey
Who trusts Liuyi Yao overall
Papers from Liuyi Yao's perspective
Ordered by how strongly the researchers Liuyi Yao trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- A Survey on Causal Inference (2020) — 690 citations
- Representation Learning for Treatment Effect Estimation from Observational Data (2018) — 348 citations