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ORCIDJiaqi Zhang 0006
Person information
- affiliation: Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, Cambridge, MA, USA
Other persons with the same name
- Jiaqi Zhang — disambiguation page
- Jiaqi Zhang 0001
![[0000-0002-8833-1714]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0002-8833-1714")
— Tsinghua University, Beijing, China - Jiaqi Zhang 0002 — University of Florida, Gainesville, FL, USA
- Jiaqi Zhang 0003 — Chongqing University of Technology, College of Computer Science and Engineering, Chongqing, China
- Jiaqi Zhang 0004 — University of Queensland, Brisbane, Australia (and 1 more)
- Jiaqi Zhang 0005 — Brown University, Department of Computer Science, Providence, RI, USA
- Jiaqi Zhang 0007 — Peking University, School of Computer Science, State Key Laboratory of Multimedia Information Processing, Beijing, China (and 1 more)
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2020 – today
- 2026
[j3]Emily Liu, Jiaqi Zhang, Caroline Uhler:
Learning genetic perturbation effects with variational causal inference. PLoS Comput. Biol. 22(2): 1013194 (2026)- [i14]Lars Lorch, Jiaqi Zhang, Charlotte Bunne, Andreas Krause, Bernhard Schölkopf, Caroline Uhler:
Latent Causal Diffusions for Single-Cell Perturbation Modeling. CoRR abs/2601.15341 (2026) - [i13]Marc Franquesa Monés, Jiaqi Zhang, Caroline Uhler:
On the Number of Conditional Independence Tests in Constraint-based Causal Discovery. CoRR abs/2603.21844 (2026) - 2025
- [c9]Divya Shyamal, Jiaqi Zhang, Caroline Uhler:
Probabilistic Factorial Experimental Design for Combinatorial Interventions. ICML 2025 - [c8]Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong, Yuan Gong, Jiaqi Zhang, Brian Tracey, Katerina Placek, Marco Vilela, Jim Glass:
Can Diffusion Models Disentangle? A Theoretical Perspective. NeurIPS 2025 - [i12]Liming Wang, Muhammad Jehanzeb Mirza, Yishu Gong, Yuan Gong, Jiaqi Zhang, Brian H. Tracey, Katerina Placek, Marco Vilela, James R. Glass:
Can Diffusion Models Disentangle? A Theoretical Perspective. CoRR abs/2504.00220 (2025) - [i11]Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler:
Meta-Dependence in Conditional Independence Testing. CoRR abs/2504.12594 (2025) - [i10]Divya Shyamal, Jiaqi Zhang, Caroline Uhler:
Probabilistic Factorial Experimental Design for Combinatorial Interventions. CoRR abs/2506.03363 (2025) - [i9]Caroline Uhler, Jiaqi Zhang:
Causal Structure and Representation Learning with Biomedical Applications. CoRR abs/2511.04790 (2025) - 2024
- [c7]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Queries. AISTATS 2024: 3925-3933 - [c6]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. ICML 2024: 45060-45078 - [c5]Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma:
Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. ICML 2024: 59042-59065 - [c4]Ryan Welch, Jiaqi Zhang, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. NeurIPS 2024 - [i8]Jiaqi Zhang, Kirankumar Shiragur, Caroline Uhler:
Membership Testing in Markov Equivalence Classes via Independence Query Oracles. CoRR abs/2403.05759 (2024) - [i7]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Causal Discovery with Fewer Conditional Independence Tests. CoRR abs/2406.01823 (2024) - [i6]Ryan Welch, Jiaqi Zhang, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data. CoRR abs/2410.23620 (2024) - 2023
- [j2]Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active learning for optimal intervention design in causal models. Nat. Mac. Intell. 5(10): 1066-1075 (2023) - [c3]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. NeurIPS 2023 - [c2]Jiaqi Zhang, Kristjan H. Greenewald, Chandler Squires, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. NeurIPS 2023 - [i5]Jiaqi Zhang, Chandler Squires, Kristjan H. Greenewald, Akash Srivastava, Karthikeyan Shanmugam, Caroline Uhler:
Identifiability Guarantees for Causal Disentanglement from Soft Interventions. CoRR abs/2307.06250 (2023) - [i4]Jiaqi Zhang, Joel Jennings, Cheng Zhang, Chao Ma:
Towards Causal Foundation Model: on Duality between Causal Inference and Attention. CoRR abs/2310.00809 (2023) - [i3]Kirankumar Shiragur, Jiaqi Zhang, Caroline Uhler:
Meek Separators and Their Applications in Targeted Causal Discovery. CoRR abs/2310.20075 (2023) - 2022
- [j1]Jiaqi Zhang, Zeyu Jin, Bo Jiang, Zaiwen Wen:
Stochastic Augmented Projected Gradient Methods for the Large-Scale Precoding Matrix Indicator Selection Problem. IEEE Trans. Wirel. Commun. 21(11): 9553-9565 (2022) - [i2]Jiaqi Zhang, Louis Cammarata, Chandler Squires, Themistoklis P. Sapsis, Caroline Uhler:
Active Learning for Optimal Intervention Design in Causal Models. CoRR abs/2209.04744 (2022) - 2021
- [c1]Jiaqi Zhang, Chandler Squires, Caroline Uhler:
Matching a Desired Causal State via Shift Interventions. NeurIPS 2021: 19923-19934 - [i1]Jiaqi Zhang, Chandler Squires, Caroline Uhler:
Matching a Desired Causal State via Shift Interventions. CoRR abs/2107.01850 (2021)
Coauthor Index
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