Proceedings of the 16th ACM SIGKDD international conference on Knowledge … Estimation of a structural vector autoregression model using non-gaussianity. D Janzing, J Mooij, K Zhang, J Lemeire, J...

Kun Zhang is an associate professor in the CMU philosophy department and an affiliate faculty member in the machine learning department. His research interests lie in machine learning and artificial intelligence, especially in causal discovery and causality-based learning.

I am an associate professor in the philosophy department and an affiliate faculty member in the machine learning department at Carnegie Mellon University.

Professor Zhang is a general and program chair of the 1st Conference on Causal Learning and Reasoning (CleaR 2022) and a program chair of the 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022). Senior research scientist at the Max-Planck Institute for Intelligent Systems, Germany.

My research interests lie in machine learning and artificial intelligence, especially in causal discovery, causal representation learning, and causality-based learning, aiming to make hidden entities and causal processes transparent for the purpose of automated scientific discovery, optimal decision making, etc.

Kun Zhang Professor, Mohamed bin Zayed University of Artificial Intelligence Associate Professor, Carnegie Mellon University. Joined ; April 2017

卡内基梅隆大学哲学系助理教授和机器学习系副教授，研究兴趣是机器学习和人工智能，尤其是因果发现、基于因果关系的学习和通用人工智能。 曾担任大型机器学习或人工智能会议的区域主席或高级程序委员会成员，包括NeurIPS、UAI、ICML、AISTATS、AAAI和IJCAI。 个人主页：https://www.cmu.edu/dietrich/philosophy/people/faculty/zhang.html. https://www.cmu.edu/dietrich/philosophy/people/faculty/zhang.html …

Kun Zhang. Associate Professor Department Philosophy. Research Interests Artificial Intelligence. Advisees Lingjing Kong. Computer Science Department. Carnegie Mellon University. 5000 Forbes Avenue. Pittsburgh, PA 15213. Fax: 412-268-5576 . Pittsburgh Campus; Qatar Campus;

estimating latent variables and their relations in the linear-Gaussian case: a versatile rank deficiency-based approach, known as Rank-based Latent Causal Discovery (RLCD), applications to psychometrical studies (Dong et al., ICLR'24) and parameter identifiability (Dong et al., NeurIPS'24) and and its earlier version that does not allow causal l...

Currently, I am a Postdoctoral Researcher at Suzhou Institute for Advanced Research, University of Science and Technology of China (USTC), advised by Prof. S. Kevin Zhou (IEEE Fellow) and Prof. Houqiang Li (IEEE Fellow).