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researcher

Lin Liu

31 papers hereh-index 425.4k citations215 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author24
  • last author4

Across the 28 of 31 papers where every author was matched, so the position is known.

fields
  • cs.LG13
  • cs.AI11
  • stat.ME4
  • cs.CY1
  • cs.DB1
  • q-bio.GN1
same name
  • Lin Liu — 25 papers, h 10
  • Lin Liu — 21 papers, h 7
  • Lin Liu — 16 papers, h 6
  • Lin Liu — 14 papers, h 11
  • Lin Liu — 13 papers, h 14
  • Lin Liu — 13 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152023
most citedA fast PC algorithm for high dimensional causal discovery with multi-core PCs

144 citations · 424 across the 30 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.LG2022

Causal Inference with Conditional Instruments using Deep Generative Models

Debo Cheng, Ziqi Xu, Jiuyong Li +3

The instrumental variable (IV) approach is a widely used way to estimate the causal effects of a treatment on an outcome of interest from observational data with latent confounders…

cs.AI2022★ 4 cited

Data-Driven Causal Effect Estimation Based on Graphical Causal Modelling: A Survey

Debo Cheng, Jiuyong Li, Lin Liu +2

In many fields of scientific research and real-world applications, unbiased estimation of causal effects from non-experimental data is crucial for understanding the mechanism under…

cs.LG2022★ 8 cited

Disentangled Representation with Causal Constraints for Counterfactual Fairness

Ziqi Xu, Jixue Liu, Debo Cheng +3

Much research has been devoted to the problem of learning fair representations; however, they do not explicitly the relationship between latent representations. In many real-world…

cs.AI2022★ 2 cited

Ancestral Instrument Method for Causal Inference without Complete Knowledge

Debo Cheng, Jiuyong Li, Lin Liu +3

Unobserved confounding is the main obstacle to causal effect estimation from observational data. Instrumental variables (IVs) are widely used for causal effect estimation when ther…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.