Causal Effect Inference with Deep Latent-Variable Models

24 May 2017

Joris Mooij

Papers citing "Causal Effect Inference with Deep Latent-Variable Models"

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Title
Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysis Chainarong Amornbunchornvej Navaporn Surasvadi Anon Plangprasopchok S. Thajchayapong 14 4 0 12 May 2022
Machine Learning based Framework for Robust Price-Sensitivity Estimation with Application to Airline Pricing Ravi Kumar Shahin Boluki Karl Isler Jonas Rauch Darius Walczak OOD 19 1 0 04 May 2022
Partial Identification of Dose Responses with Hidden Confounders Myrl G. Marmarelis E. Haddad Andrew Jesson N. Jahanshad Aram Galstyan Greg Ver Steeg CML 33 7 0 24 Apr 2022
Do learned representations respect causal relationships? Lan Wang Vishnu Naresh Boddeti NAI CML OOD 29 6 0 02 Apr 2022
Personalized Prediction of Future Lesion Activity and Treatment Effect in Multiple Sclerosis from Baseline MRI J. Durso-Finley J. Falet Brennan Nichyporuk Douglas L. Arnold Tal Arbel AI4CE 6 9 0 01 Apr 2022
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong GAN OOD CML 27 6 0 01 Apr 2022
Treatment Learning Causal Transformer for Noisy Image Classification Chao-Han Huck Yang I-Te Danny Hung Yi-Chieh Liu Pin-Yu Chen ViT 21 7 0 29 Mar 2022
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies Shachi Deshpande Kaiwen Wang Dhruv Sreenivas Zheng Li Volodymyr Kuleshov CML SyDa 8 11 0 18 Mar 2022
Undersmoothing Causal Estimators with Generative Trees Damian Machlanski Spyridon Samothrakis Paul Clarke CML 23 1 0 16 Mar 2022
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation Kan Chen Qishuo Yin Q. Long CML 12 5 0 07 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter S. Murphy J. Pineau CML 16 9 0 28 Feb 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 47 29 0 25 Feb 2022
Predicting the impact of treatments over time with uncertainty aware neural differential equations E. Brouwer J. Hernández Stephanie L. Hyland OOD CML 22 25 0 24 Feb 2022
Deep Recurrent Modelling of Granger Causality with Latent Confounding Zexuan Yin P. Barucca CML BDL 18 12 0 23 Feb 2022
Partial Identification with Noisy Covariates: A Robust Optimization Approach Wenshuo Guo Mingzhang Yin Yixin Wang Michael I. Jordan 26 19 0 22 Feb 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 29 69 0 21 Feb 2022
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics M. Vowels S. Akbari Necati Cihan Camgöz Richard Bowden 9 4 0 18 Feb 2022
Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health records Shishir Rao M. Mamouei G. Salimi-Khorshidi Yikuan Li R. Ramakrishnan A. Hassaine D. Canoy K. Rahimi OOD CML 14 22 0 07 Feb 2022
Diversify and Disambiguate: Learning From Underspecified Data Yoonho Lee Huaxiu Yao Chelsea Finn 210 64 0 07 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 50 0 07 Feb 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation Yi-Fan Zhang Hanlin Zhang Zachary Chase Lipton Li Erran Li Eric P. Xing OODD 24 29 0 02 Feb 2022
A Causal Lens for Controllable Text Generation Zhiting Hu Erran L. Li 45 59 0 22 Jan 2022
REST: Debiased Social Recommendation via Reconstructing Exposure Strategies Ruichu Cai Fengzhu Wu Zijian Li Jie Qiao Wei Chen Yuexing Hao Hao Gu CML OffRL 18 5 0 13 Jan 2022
Deep Causal Reasoning for Recommendations Yaochen Zhu Jing Yi Jiayi Xie Zhenzhong Chen CML BDL 27 10 0 06 Jan 2022
Deep Treatment-Adaptive Network for Causal Inference Qian Li Zhichao Wang Shaowu Liu Gang Li Guandong Xu CML BDL OOD 14 10 0 27 Dec 2021
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies Lu Cheng Ruocheng Guo Huan Liu CML 16 6 0 19 Dec 2021
Multi-treatment Effect Estimation from Biomedical Data Raquel Y. S. Aoki Yizhou Chen M. Ester 13 0 0 14 Dec 2021
Sage: Leveraging ML to Diagnose Unpredictable Performance in Cloud Microservices Yu Gan Mingyu Liang Sundar Dev David Lo Christina Delimitrou LRM 12 16 0 12 Dec 2021
Causal Knowledge Guided Societal Event Forecasting Songgaojun Deng Huzefa Rangwala Yue Ning AI4TS 24 2 0 10 Dec 2021
Non parametric estimation of causal populations in a counterfactual scenario Céline Beji Florian Yger Jamal Atif CML OOD 14 0 0 08 Dec 2021
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 47 21 0 06 Dec 2021
Dimension-Free Average Treatment Effect Inference with Deep Neural Networks Xinze Du Yingying Fan Jinchi Lv Tianshu Sun Patrick Vossler FedML 18 2 0 02 Dec 2021
AI Assurance using Causal Inference: Application to Public Policy A. Svetovidov Abdul Rahman Feras A. Batarseh CML 16 1 0 01 Dec 2021
A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment Robert Hu Dino Sejdinovic R. Evans CML 16 2 0 25 Nov 2021
Learning Conditional Invariance through Cycle Consistency M. Samarin V. Nesterov Mario Wieser Aleksander Wieczorek S. Parbhoo Volker Roth 39 3 0 25 Nov 2021
A Large Scale Benchmark for Individual Treatment Effect Prediction and Uplift Modeling Eustache Diemert Artem Betlei Christophe Renaudin Massih-Reza Amini T. Gregoir Thibaud Rahier CML 25 10 0 19 Nov 2021
Causal Effect Variational Autoencoder with Uniform Treatment Daniel Jiwoong Im Kyunghyun Cho N. Razavian OOD CML BDL 10 9 0 16 Nov 2021
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects N. M. Kinyanjui Fredrik D. Johansson CML 20 0 0 12 Nov 2021
Variational Auto-Encoder Architectures that Excel at Causal Inference Negar Hassanpour Russell Greiner BDL CML 14 3 0 11 Nov 2021
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries Pablo Sánchez-Martín Miriam Rateike Isabel Valera CML BDL 31 14 0 27 Oct 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 14 29 0 26 Oct 2021
Causal Effect Estimation using Variational Information Bottleneck Zhenyu Lu Yurong Cheng Mingjun Zhong G. Stoian Ye Yuan Guoren Wang CML 11 3 0 26 Oct 2021
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 35 14 0 11 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 34 6 0 04 Oct 2021
Algorithm Fairness in AI for Medicine and Healthcare Richard J. Chen Tiffany Y. Chen Jana Lipkova Judy J. Wang Drew F. K. Williamson Ming Y. Lu S. Sahai Faisal Mahmood FaML 73 45 0 01 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 27 3 0 30 Sep 2021
Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals Wasim Ahmad M. Shadaydeh Joachim Denzler BDL CML 11 4 0 22 Sep 2021
LDC-VAE: A Latent Distribution Consistency Approach to Variational AutoEncoders Xiaoyu Chen Chen Gong Qiang He Xinwen Hou Yu Liu 28 1 0 22 Sep 2021
Fairness without the sensitive attribute via Causal Variational Autoencoder Vincent Grari Sylvain Lamprier Marcin Detyniecki 24 26 0 10 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 14 3 0 08 Sep 2021