Adapting Neural Networks for the Estimation of Treatment Effects

5 June 2019

Papers citing "Adapting Neural Networks for the Estimation of Treatment Effects"

23 / 73 papers shown

Title
Estimating average causal effects from patient trajectories Dennis Frauen Tobias Hatt Valentyn Melnychuk Stefan Feuerriegel OOD CML 19 25 0 02 Mar 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
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 35 69 0 21 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 28 30 0 02 Feb 2022
Multi-treatment Effect Estimation from Biomedical Data Raquel Y. S. Aoki Yizhou Chen M. Ester 18 0 0 14 Dec 2021
Enhancing Counterfactual Classification via Self-Training Ruijiang Gao Max Biggs Wei-Ju Sun Ligong Han CML OffRL 34 6 0 08 Dec 2021
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific Andrew Jesson P. Manshausen A. Douglas D. Watson‐Parris Y. Gal P. Stier AI4Cl 27 6 0 28 Oct 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 30 30 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
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark Yaobin Ling Pulakesh Upadhyaya Luyao Chen Xiaoqian Jiang Yejin Kim CML 22 18 0 27 Sep 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 26 16 0 04 Sep 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 36 13 0 22 Jun 2021
Robust Orthogonal Machine Learning of Treatment Effects Yiyan Huang Cheuk Hang Leung Qi Wu Xing Yan OOD CML 16 0 0 22 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 25 68 0 14 Mar 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 21 31 0 16 Feb 2021
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models Severi Rissanen Pekka Marttinen CML 25 27 0 12 Feb 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 164 35 0 21 Jan 2021
RealCause: Realistic Causal Inference Benchmarking Brady Neal Chin-Wei Huang Sunand Raghupathi CML ELM 25 31 0 30 Nov 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments Shonosuke Harada H. Kashima CML 27 21 0 29 Sep 2020
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 31 27 0 27 Aug 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 30 105 0 27 Feb 2020
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 720 0 12 May 2016