Deep Causal Learning: Representation, Discovery and Inference

Deep Causal Learning: Representation, Discovery and Inference

7 November 2022

Papers citing "Deep Causal Learning: Representation, Discovery and Inference"

19 / 19 papers shown

Title
CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data Disheng Liu Yiran Qiao Wuche Liu Yiren Lu Yunlai Zhou Tuo Liang Yu Yin Jing Ma CML 3DV 54 0 0 06 Mar 2025
CASR: Refining Action Segmentation via Marginalizing Frame-levle Causal Relationships Keqing Du Xinyu Yang Hang Chen CML 19 1 0 21 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 31 2 0 02 Nov 2023
Causal reasoning in typical computer vision tasks Kexuan Zhang Qiyu Sun Chaoqiang Zhao Yang Tang CML 13 5 0 26 Jul 2023
Causal Discovery from Temporal Data: An Overview and New Perspectives Chang Gong Di Yao Chuzhe Zhang Wenbin Li Jingping Bi AI4TS CML 11 17 0 17 Mar 2023
A Survey of Deep Causal Models and Their Industrial Applications Zongyu Li Xiaoning Guo Siwei Qiang CML AI4CE 11 7 0 19 Sep 2022
An improved neural network model for treatment effect estimation Niki Kiriakidou Christos Diou CML 30 3 0 23 May 2022
Improving Multi-Task Generalization via Regularizing Spurious Correlation Ziniu Hu Zhe Zhao Xinyang Yi Tiansheng Yao Lichan Hong Yizhou Sun Ed H. Chi OOD LRM 64 29 0 19 May 2022
ML4C: Seeing Causality Through Latent Vicinity Haoyue Dai Rui Ding Yuanyuan Jiang Shi Han Dongmei Zhang OOD 27 8 0 01 Oct 2021
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation Thien Q. Tran Kazuto Fukuchi Youhei Akimoto Jun Sakuma CML 18 10 0 09 Sep 2021
NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge Xiangyuan Sun Oliver Schulte Guiliang Liu Pascal Poupart CML BDL 33 18 0 09 Sep 2021
Relating Graph Neural Networks to Structural Causal Models Matej Zečević D. Dhami Petar Velickovic Kristian Kersting AI4CE CML 47 53 0 09 Sep 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 160 49 0 03 Jun 2021
Instance-wise Causal Feature Selection for Model Interpretation Pranoy Panda Sai Srinivas Kancheti V. Balasubramanian CML 27 14 0 26 Apr 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 148 35 0 21 Jan 2021
Causal Adversarial Network for Learning Conditional and Interventional Distributions Raha Moraffah Bahman Moraffah Mansooreh Karami A. Raglin Huan Liu OOD GAN CML 44 21 0 26 Aug 2020
Explaining Visual Models by Causal Attribution Álvaro Parafita Jordi Vitrià CML FAtt 54 35 0 19 Sep 2019
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 205 713 0 12 May 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 245 9,042 0 06 Jun 2015