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Jiji Zhang
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2020 – today
- 2024
- [j17]Zhuangyan Fang
, Shengyu Zhu
On Low-Rank Directed Acyclic Graphs and Causal Structure Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4924-4937 (2024) - [i18]Guang-Yuan Hao, Jiji Zhang, Biwei Huang, Hao Wang, Kun Zhang:
Natural Counterfactuals With Necessary Backtracking. CoRR abs/2402.01607 (2024) - 2023
- [j16]Zeyu Tang
What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective. ACM Comput. Surv. 55(13s): 299:1-299:37 (2023) - [j15]Debo Cheng
Local Search for Efficient Causal Effect Estimation. IEEE Trans. Knowl. Data Eng. 35(9): 8823-8837 (2023) - [c25]Jingzhi Fang, Jiji Zhang:
A Characterization of Lewisian Causal Models. LORI 2023: 94-108 - 2022
- [c24]Debo Cheng
Ancestral Instrument Method for Causal Inference without Complete Knowledge. IJCAI 2022: 4843-4849 - [c23]Amin Jaber, Adèle H. Ribeiro, Jiji Zhang, Elias Bareinboim:
Causal Identification under Markov equivalence: Calculus, Algorithm, and Completeness. NeurIPS 2022 - [c22]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a neural conditional dependence measure. UAI 2022: 1782-1791 - [i17]Debo Cheng, Jiuyong Li, Lin Liu, Jiji Zhang, Thuc Duy Le, Jixue Liu:
Ancestral instrument method for causal inference without a causal graph. CoRR abs/2201.03810 (2022) - [i16]Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang:
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. CoRR abs/2201.05666 (2022) - [i15]Yimu Yin, Jiji Zhang:
Markov categories, causal theories, and the do-calculus. CoRR abs/2204.04821 (2022) - [i14]Zeyu Tang
What-Is and How-To for Fairness in Machine Learning: A Survey, Reflection, and Perspective. CoRR abs/2206.04101 (2022) - [i13]Xinwei Shen, Shengyu Zhu, Jiji Zhang, Shoubo Hu, Zhitang Chen:
Reframed GES with a Neural Conditional Dependence Measure. CoRR abs/2206.08531 (2022) - [i12]Yike Guo, Qifeng Liu, Jie Chen, Wei Xue, Henrik J. Jensen, Fernando Rosas, Jeffrey Shaw, Xing Wu, Jiji Zhang, Jianliang Xu:
Pathway to Future Symbiotic Creativity. CoRR abs/2209.02388 (2022) - 2021
- [j14]Jiji Zhang
Subjective causal networks and indeterminate suppositional credences. Synth. 198(27): 6571-6597 (2021) - [c21]Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang:
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions. NeurIPS 2021: 20308-20320 - 2020
- [j13]Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf:
Causal Discovery from Heterogeneous/Nonstationary Data. J. Mach. Learn. Res. 21: 89:1-89:53 (2020) - [c20]Hanti Lin, Jiji Zhang:
On Learning Causal Structures from Non-Experimental Data without Any Faithfulness Assumption. ALT 2020: 554-582 - [i11]Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He:
Low Rank Directed Acyclic Graphs and Causal Structure Learning. CoRR abs/2006.05691 (2020)
2010 – 2019
- 2019
- [c19]Amin Jaber, Jiji Zhang, Elias Bareinboim:
Causal Identification under Markov Equivalence: Completeness Results. ICML 2019: 2981-2989 - [c18]Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions. IJCAI 2019: 1488-1494 - [c17]Amin Jaber, Jiji Zhang, Elias Bareinboim:
On Causal Identification under Markov Equivalence. IJCAI 2019: 6181-6185 - [c16]Amin Jaber, Jiji Zhang, Elias Bareinboim:
Identification of Conditional Causal Effects under Markov Equivalence. NeurIPS 2019: 11512-11520 - [i10]Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero
Causal Discovery from Heterogeneous/Nonstationary Data. CoRR abs/1903.01672 (2019) - [i9]Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer, Mark Junjie Li:
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions. CoRR abs/1906.02385 (2019) - 2018
- [j12]Jiji Zhang
Agreeing to disagree and dilation. Int. J. Approx. Reason. 101: 150-162 (2018) - [c15]Amin Jaber, Jiji Zhang, Elias Bareinboim:
A Graphical Criterion for Effect Identification in Equivalence Classes of Causal Diagrams. IJCAI 2018: 5024-5030 - [c14]Amin Jaber, Jiji Zhang, Elias Bareinboim:
Causal Identification under Markov Equivalence. UAI 2018: 978-987 - [i8]Hanti Lin, Jiji Zhang:
How to Tackle an Extremely Hard Learning Problem: Learning Causal Structures from Non-Experimental Data without the Faithfulness Assumption or the Like. CoRR abs/1802.07051 (2018) - [i7]Amin Jaber, Jiji Zhang, Elias Bareinboim:
Causal Identification under Markov Equivalence. CoRR abs/1812.06209 (2018) - 2017
- [j11]Zhalama, Jiji Zhang
Weakening faithfulness: some heuristic causal discovery algorithms. Int. J. Data Sci. Anal. 3(2): 93-104 (2017) - [c13]Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero
Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. ICDM 2017: 913-918 - [c12]Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. IJCAI 2017: 1347-1353 - [c11]Jiji Zhang, Hailin Liu, Teddy Seidenfeld:
Agreeing to Disagree and Dilation. ISIPTA 2017: 370-381 - [c10]Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer:
SAT-Based Causal Discovery under Weaker Assumptions. UAI 2017 - 2016
- [j10]Jiji Zhang
The three faces of faithfulness. Synth. 193(4): 1011-1027 (2016) - [j9]Kun Zhang, Zhikun Wang, Jiji Zhang
On Estimation of Functional Causal Models: General Results and Application to the Post-Nonlinear Causal Model. ACM Trans. Intell. Syst. Technol. 7(2): 13:1-13:22 (2016) - [c9]Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour:
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. UAI 2016 - 2015
- [i6]Kun Zhang, Jiji Zhang, Bernhard Schölkopf:
Distinguishing Cause from Effect Based on Exogeneity. CoRR abs/1504.05651 (2015) - 2013
- [j8]Jiji Zhang
A Peculiarity in Pearl's Logic of Interventionist Counterfactuals. J. Philos. Log. 42(5): 783-794 (2013) - [j7]Jiji Zhang
A Lewisian Logic of Causal Counterfactuals. Minds Mach. 23(1): 77-93 (2013) - 2012
- [i5]Jiji Zhang:
A Characterization of Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. CoRR abs/1206.5282 (2012) - [i4]Joseph D. Ramsey, Jiji Zhang, Peter Spirtes:
Adjacency-Faithfulness and Conservative Causal Inference. CoRR abs/1206.6843 (2012) - [i3]Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang:
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. CoRR abs/1207.1365 (2012) - [i2]Jiji Zhang, Peter Spirtes:
A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables. CoRR abs/1207.1419 (2012) - [i1]Jiji Zhang, Peter Spirtes:
Strong Faithfulness and Uniform Consistency in Causal Inference. CoRR abs/1212.2506 (2012) - 2011
- [j6]Jiji Zhang
Intervention, determinism, and the causal minimality condition. Synth. 182(3): 335-347 (2011) - [c8]Jiji Zhang, Ricardo Bezerra de Andrade e Silva:
Discussion of "Learning Equivalence Classes of Acyclic Models with Latent and Selection Variables from Multiple Datasets with Overlapping Variables". AISTATS 2011: 16-18 - 2010
- [j5]Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang
Actual causation: a stone soup essay. Synth. 175(2): 169-192 (2010)
2000 – 2009
- 2008
- [j4]Jiji Zhang
On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias. Artif. Intell. 172(16-17): 1873-1896 (2008) - [j3]Jiji Zhang:
Causal Reasoning with Ancestral Graphs. J. Mach. Learn. Res. 9: 1437-1474 (2008) - [j2]Jiji Zhang
Detection of Unfaithfulness and Robust Causal Inference. Minds Mach. 18(2): 239-271 (2008) - [j1]Jiji Zhang
Error probabilities for inference of causal directions. Synth. 163(3): 409-418 (2008) - 2007
- [c7]Jiji Zhang:
A Characterization of Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. UAI 2007: 450-457 - [c6]Jiji Zhang:
Generalized Do-Calculus with Testable Causal Assumptions. AISTATS 2007: 667-674 - 2006
- [c5]Joseph D. Ramsey, Jiji Zhang, Peter Spirtes:
Adjacency-Faithfulness and Conservative Causal Inference. UAI 2006 - 2005
- [c4]Ricardo Bezerra de Andrade e Silva, Jiji Zhang
Probabilistic workflow mining. KDD 2005: 275-284 - [c3]Ayesha R. Ali, Thomas S. Richardson, Peter Spirtes, Jiji Zhang:
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables. UAI 2005: 10-17 - [c2]Jiji Zhang, Peter Spirtes:
A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables. UAI 2005: 667-674 - 2003
- [c1]Jiji Zhang, Peter Spirtes:
Strong Faithfulness and Uniform Consistency in Causal Inference. UAI 2003: 632-639
Coauthor Index
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