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Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders

1 February 2019

Papers citing "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders"

35 / 35 papers shown

Title
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity Yahya Aalaila Gerrit Großmann Sumantrak Mukherjee Jonas Wahl Sebastian Vollmer CML LRM 140 0 0 31 Mar 2025
DeCaFlow: A Deconfounding Causal Generative Model Alejandro Almodóvar Adrián Javaloy J. Parras Santiago Zazo Isabel Valera CML 69 0 0 19 Mar 2025
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 73 2 0 01 Mar 2024
Right on Time: Revising Time Series Models by Constraining their Explanations Maurice Kraus David Steinmann Antonia Wüst Andre Kokozinski Kristian Kersting AI4TS 74 4 0 20 Feb 2024
Clairvoyance: A Pipeline Toolkit for Medical Time Series Daniel Jarrett Jinsung Yoon Ioana Bica Zhaozhi Qian A. Ercole M. Schaar AI4TS 87 36 0 28 Oct 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 212 2 0 16 Oct 2023
CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction Zhoujian Sun Wenzhuo Zhang Zhengxing Huang Nai Ding Cheng Luo CML 91 2 0 18 Aug 2023
Deep Causal Learning for Robotic Intelligence Yongqian Li CML 73 5 0 23 Dec 2022
On How AI Needs to Change to Advance the Science of Drug Discovery Kieran Didi Matej Zečević CML 62 1 0 23 Dec 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 70 22 0 08 Oct 2022
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions V. T. Trifunov M. Shadaydeh Joachim Denzler CML BDL 59 3 0 23 Sep 2022
Estimating individual treatment effects under unobserved confounding using binary instruments Dennis Frauen Stefan Feuerriegel CML 85 20 0 17 Aug 2022
Variational Temporal Deconfounder for Individualized Treatment Effect Estimation from Longitudinal Observational Data Zheng Feng M. Prosperi Jiang Bian CML 42 0 0 23 Jul 2022
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat F. Imrie Alexis Bellot Zhaozhi Qian M. Schaar OOD CML 57 52 0 16 Jun 2022
Deconfounding Actor-Critic Network with Policy Adaptation for Dynamic Treatment Regimes Changchang Yin Ruoqi Liu Jeffrey Caterino Ping Zhang OffRL 90 5 0 19 May 2022
Estimating average causal effects from patient trajectories Dennis Frauen Tobias Hatt Valentyn Melnychuk Stefan Feuerriegel OOD CML 95 25 0 02 Mar 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 90 32 0 25 Feb 2022
Causal Knowledge Guided Societal Event Forecasting Songgaojun Deng Huzefa Rangwala Yue Ning AI4TS 61 2 0 10 Dec 2021
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 94 22 0 06 Dec 2021
A Taxonomy for Inference in Causal Model Families Matej Zevcević Devendra Singh Dhami Kristian Kersting 76 1 0 22 Oct 2021
Relating Graph Neural Networks to Structural Causal Models Matej Zečević Devendra Singh Dhami Petar Velickovic Kristian Kersting AI4CE CML 134 56 0 09 Sep 2021
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction Siyuan Ren Bin Guo LongBing Cao Ke Li Jiaqi Liu Zhiwen Yu 40 8 0 18 Aug 2021
Adaptive Multi-Source Causal Inference Thanh Vinh Vo Pengfei Wei T. Hoang Tze-Yun Leong 87 1 0 31 May 2021
Federated Estimation of Causal Effects from Observational Data Thanh Vinh Vo T. Hoang Young Lee Tze-Yun Leong FedML CML 70 13 0 31 May 2021
Sequential Deconfounding for Causal Inference with Unobserved Confounders Tobias Hatt Stefan Feuerriegel CML 95 29 0 16 Apr 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments S. Parbhoo Stefan Bauer Patrick Schwab CML BDL 60 16 0 20 Mar 2021
Towards Causal Representation Learning Bernhard Schölkopf Francesco Locatello Stefan Bauer Nan Rosemary Ke Nal Kalchbrenner Anirudh Goyal Yoshua Bengio OOD CML AI4CE 155 322 0 22 Feb 2021
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models Matej Zečević Devendra Singh Dhami Athresh Karanam S. Natarajan Kristian Kersting CML TPM 89 33 0 20 Feb 2021
Causal Inference for Time series Analysis: Problems, Methods and Evaluation Raha Moraffah Paras Sheth Mansooreh Karami Anchit Bhattacharya Qianru Wang Anique Tahir A. Raglin Huan Liu CML AI4TS 106 110 0 11 Feb 2021
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 90 27 0 27 Aug 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 90 106 0 27 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 117 516 0 05 Feb 2020
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang Yixin Wang A. Ostropolets J. J. Mulgrave David M. Blei G. Hripcsak BDL CML 136 1 0 03 Apr 2019
Weighted Tensor Completion for Time-Series Causal Inference Debmalya Mandal David C. Parkes 19 2 0 12 Feb 2019