no code implementations • 10 Nov 2024 • Yuewen Sun, Lingjing Kong, Guangyi Chen, Loka Li, Gongxu Luo, Zijian Li, Yixuan Zhang, Yujia Zheng, Mengyue Yang, Petar Stojanov, Eran Segal, Eric P. Xing, Kun Zhang
Theoretically, we consider a flexible nonparametric latent distribution (c. f., parametric assumptions in prior work) permitting causal relationships across potentially different modalities.
1 code implementation • 24 Jul 2024 • Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang
Linear causal models are important tools for modeling causal dependencies and yet in practice, only a subset of the variables can be observed.
no code implementations • 21 Apr 2024 • Donghuo Zeng, Roberto S. Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang
In this paper, we present a novel approach that tracks a user's latent personality dimensions (LPDs) during ongoing persuasion conversation and generates tailored counterfactual utterances based on these LPDs to optimize the overall persuasion outcome.
1 code implementation • 25 Jan 2024 • Guangyi Chen, Yifan Shen, Zhenhao Chen, Xiangchen Song, Yuewen Sun, Weiran Yao, Xiao Liu, Kun Zhang
Identifying the underlying time-delayed latent causal processes in sequential data is vital for grasping temporal dynamics and making downstream reasoning.
no code implementations • 30 Dec 2023 • Shuo Xu, Yucheng Zhang, Gang Chen, Xincheng Xiang, Peng Cong, Yuewen Sun
In this study, we propose a fully unsupervised framework called Deep Radon Prior (DRP), inspired by Deep Image Prior (DIP), to address the aforementioned limitations.
2 code implementations • 11 Oct 2021 • Weiran Yao, Yuewen Sun, Alex Ho, Changyin Sun, Kun Zhang
In this work, we consider both a nonparametric, nonstationary setting and a parametric setting for the latent processes and propose two provable conditions under which temporally causal latent processes can be identified from their nonlinear mixtures.
2 code implementations • ICLR 2022 • Weiran Yao, Yuewen Sun, Alex Ho, Changyin Sun, Kun Zhang
Our goal is to find time-delayed latent causal variables and identify their relations from temporal measured variables.