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Discovery and Visualization of Nonstationary Causal Models
v1v2v3 (latest)

Discovery and Visualization of Nonstationary Causal Models

27 September 2015
Kun Zhang
Erdun Gao
Jiji Zhang
Bernhard Schölkopf
Clark Glymour
    CML
ArXiv (abs)PDFHTML

Papers citing "Discovery and Visualization of Nonstationary Causal Models"

10 / 10 papers shown
When Selection Meets Intervention: Additional Complexities in Causal Discovery
When Selection Meets Intervention: Additional Complexities in Causal DiscoveryInternational Conference on Learning Representations (ICLR), 2025
Haoyue Dai
Ignavier Ng
Jianle Sun
Zeyu Tang
Gongxu Luo
Xinshuai Dong
Peter Spirtes
Kun Zhang
CML
426
6
0
10 Mar 2025
Federated Causal Discovery from Heterogeneous Data
Federated Causal Discovery from Heterogeneous Data
Loka Li
Ignavier Ng
Gongxu Luo
Erdun Gao
Guan-Hong Chen
Tongliang Liu
Bin Gu
Kun Zhang
FedML
336
16
0
20 Feb 2024
On the Three Demons in Causality in Finance: Time Resolution,
  Nonstationarity, and Latent Factors
On the Three Demons in Causality in Finance: Time Resolution, Nonstationarity, and Latent Factors
Xinshuai Dong
Haoyue Dai
Yewen Fan
Songyao Jin
Sathyamoorthy Rajendran
Kun Zhang
CML
287
1
0
28 Dec 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou
Shaoan Xie
Guang-Yuan Hao
Shiming Chen
Erdun Gao
Xiwei Xu
Chen Wang
Liming Zhu
Lina Yao
Kun Zhang
AI4CE
611
15
0
29 Jan 2023
A Subsampling-Based Method for Causal Discovery on Discrete Data
A Subsampling-Based Method for Causal Discovery on Discrete DataSymposium on Software Performance (SP), 2021
Austin V. Goddard
Yu Xiang
CML
304
1
0
31 Aug 2021
Causal Discovery from Heterogeneous/Nonstationary Data with Independent
  Changes
Causal Discovery from Heterogeneous/Nonstationary Data with Independent ChangesJournal of machine learning research (JMLR), 2019
Erdun Gao
Kun Zhang
Jiji Zhang
Joseph Ramsey
Ruben Sanchez-Romero
Clark Glymour
Bernhard Schölkopf
566
288
0
05 Mar 2019
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise
  Models
Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models
Shoubo Hu
Zhitang Chen
V. Nia
L. Chan
Yanhui Geng
CML
276
30
0
23 Sep 2018
A Kernel Embedding-based Approach for Nonstationary Causal Model
  Inference
A Kernel Embedding-based Approach for Nonstationary Causal Model Inference
Shoubo Hu
Zhitang Chen
L. Chan
CML
138
4
0
23 Sep 2018
FASK with Interventional Knowledge Recovers Edges from the Sachs Model
FASK with Interventional Knowledge Recovers Edges from the Sachs Model
Joseph Ramsey
Bryan Andrews
203
25
0
06 May 2018
Learning Causal Structures Using Regression Invariance
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami
Saber Salehkaleybar
Negar Kiyavash
Kun Zhang
OODCML
271
71
0
26 May 2017
1
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