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Counterfactual Representation Learning with Balancing Weights

23 October 2020

Lawrence Carin

Papers citing "Counterfactual Representation Learning with Balancing Weights"

21 / 21 papers shown

Title
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning Weilin Chen Ruichu Cai Zeqin Yang Jie Qiao Yuguang Yan Zijian Li Zhifeng Hao CML 79 7 0 06 May 2024
Defining Expertise: Applications to Treatment Effect Estimation Alihan Huyuk Qiyao Wei Alicia Curth M. Schaar CML 68 2 0 01 Mar 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 79 10 0 19 Nov 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
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation Abbavaram Gowtham Reddy V. Balasubramanian CML 42 0 0 08 Nov 2022
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation Ioana Bica M. Schaar OOD CML 70 22 0 08 Oct 2022
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning Ruichu Cai Weilin Chen Zeqin Yang Shu Wan Chen Zheng Xiaoqing Yang Jiecheng Guo CML BDL 94 12 0 09 Aug 2022
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability Jonathan Crabbé Alicia Curth Ioana Bica M. Schaar CML 110 16 0 16 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 63 2 0 06 Jun 2022
DÁRTAGNAN: Counterfactual Video Generation Hadrien Reynaud Athanasios Vlontzos Mischa Dombrowski Ciarán M. Gilligan-Lee A. Beqiri Paul Leeson Bernhard Kainz VGen CML MedIm 80 20 0 03 Jun 2022
Multiple Domain Causal Networks Tianhui Zhou IV WilliamE.Carson M. H. Klein David Carlson CML 32 0 0 13 May 2022
Outcome Assumptions and Duality Theory for Balancing Weights David Bruns-Smith Avi Feller 48 5 0 17 Mar 2022
Estimating Conditional Average Treatment Effects with Missing Treatment Information Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 50 6 0 02 Mar 2022
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data Alicia Curth Changhee Lee M. Schaar CML 70 30 0 26 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 208 8 0 04 Oct 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 113 17 0 04 Sep 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation Alicia Curth M. Schaar CML 193 84 0 07 Jun 2021
Learning from Counterfactual Links for Link Prediction Tong Zhao Gang Liu Daheng Wang Wenhao Yu Meng Jiang CML OOD 87 100 0 03 Jun 2021
Matched sample selection with GANs for mitigating attribute confounding Chandan Singh Guha Balakrishnan Pietro Perona GAN 69 6 0 24 Mar 2021
Robust Orthogonal Machine Learning of Treatment Effects Yiyan Huang Cheuk Hang Leung Qi Wu Xing Yan OOD CML 50 0 0 22 Mar 2021
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition Vincent Dorie J. Hill Uri Shalit M. Scott D. Cervone CML 261 288 0 09 Jul 2017