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CUTS: Neural Causal Discovery from Irregular Time-Series Data

CUTS: Neural Causal Discovery from Irregular Time-Series Data

15 February 2023
Yuxiao Cheng
Runzhao Yang
Tingxiong Xiao
Zongren Li
J. Suo
K. He
Qionghai Dai
    OOD
    BDL
    AI4TS
    CML
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Papers citing "CUTS: Neural Causal Discovery from Irregular Time-Series Data"

13 / 13 papers shown
Title
Time Series Domain Adaptation via Latent Invariant Causal Mechanism
Time Series Domain Adaptation via Latent Invariant Causal Mechanism
Ruichu Cai
Junxian Huang
Zhenhui Yang
Zijian Li
Emadeldeen Eldele
Min Wu
Gang Hua
OOD
CML
BDL
AI4TS
54
0
0
23 Feb 2025
Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care
Causally-informed Deep Learning towards Explainable and Generalizable Outcomes Prediction in Critical Care
Yuxiao Cheng
Xinxin Song
Ziqian Wang
Qin Zhong
Kunlun He
J. Suo
OOD
CML
93
0
0
04 Feb 2025
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data
Yue Cheng
Jiajun Zhang
Weiwei Xing
Xiaoyu Guo
Yue Cheng
Witold Pedrycz
CML
32
0
0
25 Oct 2024
Causal Discovery from Time-Series Data with Short-Term Invariance-Based
  Convolutional Neural Networks
Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks
Rujia Shen
Boran Wang
Chao Zhao
Yi Guan
Jingchi Jiang
CML
BDL
AI4TS
34
0
0
15 Aug 2024
CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
CausalFormer: An Interpretable Transformer for Temporal Causal Discovery
Lingbai Kong
Wengen Li
Hanchen Yang
Yichao Zhang
Jihong Guan
Shuigeng Zhou
CML
AI4TS
35
0
0
24 Jun 2024
Jacobian Regularizer-based Neural Granger Causality
Jacobian Regularizer-based Neural Granger Causality
Wanqi Zhou
Shuanghao Bai
Shujian Yu
Qibin Zhao
Badong Chen
CML
53
3
0
14 May 2024
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
Bayesian Vector AutoRegression with Factorised Granger-Causal Graphs
He Zhao
V. Kitsios
Terry O'Kane
Edwin V. Bonilla
CML
24
1
0
06 Feb 2024
Diffusion model for relational inference
Diffusion model for relational inference
Shuhan Zheng
Ziqiang Li
Kantaro Fujiwara
Gouhei Tanaka
DiffM
27
2
0
30 Jan 2024
Neural Structure Learning with Stochastic Differential Equations
Neural Structure Learning with Stochastic Differential Equations
Benjie Wang
Joel Jennings
Wenbo Gong
CML
AI4TS
23
3
0
06 Nov 2023
CausalTime: Realistically Generated Time-series for Benchmarking of
  Causal Discovery
CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery
Yuxiao Cheng
Ziqian Wang
Tingxiong Xiao
Qin Zhong
J. Suo
Kunlun He
AI4TS
CML
30
11
0
03 Oct 2023
CTP:A Causal Interpretable Model for Non-Communicable Disease
  Progression Prediction
CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction
Zhoujian Sun
Wenzhuo Zhang
Zhengxing Huang
Nai Ding
Cheng Luo
CML
41
2
0
18 Aug 2023
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
CUTS+: High-dimensional Causal Discovery from Irregular Time-series
Yuxiao Cheng
Lianglong Li
Tingxiong Xiao
Zongren Li
Qionghai Dai
J. Suo
K. He
CML
BDL
AI4TS
26
22
0
10 May 2023
Measuring and testing dependence by correlation of distances
Measuring and testing dependence by correlation of distances
G. Székely
Maria L. Rizzo
N. K. Bakirov
185
2,578
0
28 Mar 2008
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