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researcher

Junzhe Zhang

Syracuse University

11 papers hereh-index 141.1k citations36 works total

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

author position
  • first author3
  • middle author7
  • last author1

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.AI4
  • physics.chem-ph1
affiliations
  • Syracuse University
Homepage
same name
  • Junzhe Zhang — 11 papers, h 5
  • Junzhe Zhang — 4 papers, h 6
  • Junzhe Zhang — 3 papers
  • Junzhe Zhang — 2 papers
  • Junzhe Zhang — 2 papers, h 2
  • Junzhe Zhang — 2 papers, h 6

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
20212026
most citedPartial Counterfactual Identification from Observational and Experimental Data

10 citations · 10 across the 10 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

An Introduction to Causal Reinforcement Learning

Elias Bareinboim, Junzhe Zhang, Sanghack Lee

Causal inference provides a set of principles and tools that allow one to combine data and knowledge about an environment to reason with questions of counterfactual nature, i.e., w…

cs.AI2025

Confounding Robust Deep Reinforcement Learning: A Causal Approach

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

A key task in Artificial Intelligence is learning effective policies for controlling agents in unknown environments to optimize performance measures. Off-policy learning methods, l…

cs.AI2025

Automatic Reward Shaping from Confounded Offline Data

Mingxuan Li, Junzhe Zhang, Elias Bareinboim

A key task in Artificial Intelligence is learning effective policies for controlling agents in unknown environments to optimize performance measures. Off-policy learning methods, l…

cs.AI2021★ 10 cited

Partial Counterfactual Identification from Observational and Experimental Data

Junzhe Zhang, Jin Tian, Elias Bareinboim

This paper investigates the problem of bounding counterfactual queries from an arbitrary collection of observational and experimental distributions and qualitative knowledge about…

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