Causal Inference with Noisy and Missing Covariates via Matrix Factorization

3 June 2018

Papers citing "Causal Inference with Noisy and Missing Covariates via Matrix Factorization"

32 / 32 papers shown

Title
DeCaFlow: A Deconfounding Causal Generative Model Alejandro Almodóvar Adrián Javaloy J. Parras Santiago Zazo Isabel Valera CML 39 0 0 19 Mar 2025
Causal Inference with Latent Variables: Recent Advances and Future Prospectives Yaochen Zhu Yinhan He Jing Ma Mengxuan Hu Sheng Li Jundong Li CML 43 3 0 20 Jun 2024
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference Debo Cheng Yang Xie Ziqi Xu Jiuyong Li Lin Liu Jixue Liu Yinghao Zhang Zaiwen Feng CML BDL 23 1 0 08 Dec 2023
Debiasing Multimodal Models via Causal Information Minimization Vaidehi Patil A. Maharana Mohit Bansal CML 38 2 0 28 Nov 2023
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders Defu Cao James Enouen Yujing Wang Xiangchen Song Chuizheng Meng Hao Niu Yan Liu CML 35 21 0 04 Mar 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders Defu Cao James Enouen Yong-Jin Liu CML 35 2 0 19 Feb 2023
Causal Inference (C-inf) -- asymmetric scenario of typical phase transitions A. Capponi M. Stojnic 43 4 0 02 Jan 2023
Causal Inference (C-inf) -- closed form worst case typical phase transitions A. Capponi M. Stojnic 21 2 0 02 Jan 2023
Variational Temporal Deconfounder for Individualized Treatment Effect Estimation from Longitudinal Observational Data Zheng Feng M. Prosperi Jiang Bian CML 21 0 0 23 Jul 2022
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach Yuchen Zhu Limor Gultchin Arthur Gretton Matt J. Kusner Ricardo M. A. Silva CML 13 15 0 18 Jun 2022
Partial Identification with Noisy Covariates: A Robust Optimization Approach Wenshuo Guo Mingzhang Yin Yixin Wang Michael I. Jordan 31 19 0 22 Feb 2022
Evaluation Methods and Measures for Causal Learning Algorithms Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 24 51 0 07 Feb 2022
To Impute or not to Impute? Missing Data in Treatment Effect Estimation Jeroen Berrevoets F. Imrie T. Kyono James Jordon M. Schaar 28 18 0 04 Feb 2022
Deep Treatment-Adaptive Network for Causal Inference Qian Li Zhichao Wang Shaowu Liu Gang Li Guandong Xu CML BDL OOD 27 10 0 27 Dec 2021
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 50 21 0 06 Dec 2021
Causal Matrix Completion Anish Agarwal M. Dahleh Devavrat Shah Dennis Shen CML 48 51 0 30 Sep 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Conservative Policy Construction Using Variational Autoencoders for Logged Data with Missing Values Mahed Abroshan K. H. Yip Cem Tekin Mihaela van der Schaar CML OffRL 24 3 0 08 Sep 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 36 5 0 06 Aug 2021
Matrix Completion with Model-free Weighting Jiayi Wang R. K. Wong Xiaojun Mao Kwun Chuen Gary Chan 29 5 0 09 Jun 2021
Entropy Minimizing Matrix Factorization Mulin. Chen Xuelong Li 32 6 0 24 Mar 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding Pengzhou (Abel) Wu Kenji Fukumizu CML 16 13 0 17 Jan 2021
How and Why to Use Experimental Data to Evaluate Methods for Observational Causal Inference A. Gentzel Purva Pruthi David D. Jensen CML 18 18 0 06 Oct 2020
Causal Inference in Possibly Nonlinear Factor Models Yingjie Feng CML 9 7 0 31 Aug 2020
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders Andrew Bennett Nathan Kallus Lihong Li Ali Mousavi OffRL 35 43 0 27 Jul 2020
ParKCa: Causal Inference with Partially Known Causes Raquel Y. S. Aoki Martin Ester CML 16 4 0 17 Mar 2020
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models Imke Mayer Julie Josse Félix Raimundo Jean-Philippe Vert CML 29 12 0 25 Feb 2020
Optimal Experimental Design for Staggered Rollouts Ruoxuan Xiong Susan Athey Mohsen Bayati Guido Imbens 23 38 0 09 Nov 2019
Policy Evaluation with Latent Confounders via Optimal Balance Andrew Bennett Nathan Kallus CML 19 18 0 06 Aug 2019
Adapting Text Embeddings for Causal Inference Victor Veitch Dhanya Sridhar David M. Blei CML 14 21 0 29 May 2019
Imputation and low-rank estimation with Missing Not At Random data Aude Sportisse Claire Boyer Julie Josse 25 47 0 29 Dec 2018
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates S. Parbhoo Mario Wieser Aleksander Wieczorek Volker Roth CML 14 5 0 06 Jul 2018