Junzhe Zhang

Statistics and Probability · with Bareinboim · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 34 citations into it
• Artificial Intelligence — 32 citations into it; #9,618 of 35,345 by trust here, #12,083 by citations
• Causal Inference & Discovery — 22 citations into it; #128 of 364 by trust here, #120 by citations
• Sociology and Political Science — 17 citations into it; #4,234 of 22,756 by trust here, #6,353 by citations
• Reinforcement Learning — 16 citations into it; #2,124 of 2,242 by trust here, #2,160 by citations
• Safety, Robustness & Interpretability — 16 citations into it
• AI Ethics, Fairness & Society — 14 citations into it; #99 of 494 by trust here, #156 by citations
• Safety Research — 13 citations into it; #962 of 5,829 by trust here, #1,540 by citations

Whom Junzhe Zhang trusts overall

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

1. Judea Pearl
2. Elias Bareinboim
3. Susan A. Murphy
4. J. Lunceford
5. Peter Auer
6. James M. Robins
7. D. Francis
8. Donald B. Rubin
9. Kenneth A. Bollen
10. Muhammad Bilal Zafar

Who trusts Junzhe Zhang overall

1. Silvia Chiappa
2. Bernhard Schölkopf
3. Yongkai Wu
4. Elias Bareinboim
5. Maria Dimakopoulou
6. Berk Ustun
7. Julius von Kügelgen
8. Lu Zhang
9. Dino Pedreschi
10. Amir-Hossein Karimi

Papers from Junzhe Zhang's perspective

Ordered by how strongly the researchers Junzhe Zhang 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. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Et al
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Transfer Learning in Multi-Armed Bandits: A Causal Approach (2017) — 81 citations
• Fairness in Decision-Making - The Causal Explanation Formula (2018) — 326 citations
• Near-Optimal Reinforcement Learning in Dynamic Treatment Regimes (2019) — 75 citations
• Equality of Opportunity in Classification: A Causal Approach (2018) — 96 citations