Papers citing 'Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks'

Title
CausalKANs: interpretable treatment effect estimation with Kolmogorov-Arnold networks Alejandro Almodóvar Patricia A. Apellániz Santiago Zazo J. Parras CML 194 0 0 26 Sep 2025
KANITE: Kolmogorov-Arnold Networks for ITE estimation Eshan Mehendale Abhinav Thorat Ravi Kolla N. Pedanekar CML 269 2 0 18 Mar 2025
Learning Counterfactual Outcomes Under Rank Preservation Peng Wu Haoxuan Li Chunyuan Zheng Yan Zeng Jiawei Chen Yang Liu Ruocheng Guo Jianchao Tan 249 1 0 10 Feb 2025
Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML 215 0 0 07 Feb 2025
Orthogonal Representation Learning for Estimating Causal Quantities Valentyn Melnychuk Dennis Frauen Jonas Schweisthal Stefan Feuerriegel CML OOD BDL 386 5 0 06 Feb 2025
Federated Learning for Estimating Heterogeneous Treatment Effects Disha Makhija Joydeep Ghosh Yejin Kim CML FedML 296 3 0 27 Feb 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 255 19 0 19 Nov 2023
CATE Estimation With Potential Outcome Imputation From Local RegressionConference on Uncertainty in Artificial Intelligence (UAI), 2023 Ahmed Aloui Juncheng Dong Cat P. Le Vahid Tarokh CML 140 2 0 07 Nov 2023
Pareto Invariant Representation Learning for Multimedia RecommendationACM Multimedia (ACM MM), 2023 Shanshan Huang Haoxuan Li Qingsong Li Chunyuan Zheng Li Liu CML 246 17 0 09 Aug 2023
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial NetworkData mining and knowledge discovery (DMKD), 2023 Yonghe Zhao Q. Huang Haolong Zeng Yun-Wen Pen Huashan Sun CML OOD BDL 68 2 0 24 Jul 2023
Continual Causal Inference with Incremental Observational DataIEEE International Conference on Data Engineering (ICDE), 2023 Zhixuan Chu Ruopeng Li S. Rathbun Sheng Li CML 124 19 0 03 Mar 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 149 2 0 16 Jan 2023
Deep Causal Learning for Robotic IntelligenceFrontiers in Neurorobotics (Front. Neurorobot.), 2022 Yongqian Li CML 190 7 0 23 Dec 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 262 15 0 07 Nov 2022
A Survey of Deep Causal Models and Their Industrial ApplicationsArtificial Intelligence Review (Artif Intell Rev), 2022 Zongyu Li Xiaoning Guo Siwei Qiang CML AI4CE 445 14 0 19 Sep 2022
DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect EstimationKnowledge Discovery and Data Mining (KDD), 2022 Kailiang Zhong Fengtong Xiao Yan Ren Yaorong Liang Wenqing Yao Xiaofeng Yang Ling Cen CML 132 24 0 19 Jul 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure UncertaintyKnowledge Discovery and Data Mining (KDD), 2022 Christopher Tran Elena Zheleva CML 179 4 0 25 Jun 2022
Causal Balancing for Domain GeneralizationInternational Conference on Learning Representations (ICLR), 2022 Xinyi Wang Michael Stephen Saxon Jiachen Li Hongyang R. Zhang Kun Zhang William Yang Wang OOD CML 250 27 0 10 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 150 2 0 06 Jun 2022
DÁRTAGNAN: Counterfactual Video GenerationInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022 Hadrien Reynaud Athanasios Vlontzos Mischa Dombrowski Ciarán M. Gilligan-Lee A. Beqiri Paul Leeson Bernhard Kainz VGen CML MedIm 171 28 0 03 Jun 2022
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket TrialsACM Conference on Health, Inference, and Learning (ACM CHIL), 2022 Zhixuan Chu S. Rathbun Sheng Li CML 139 10 0 10 Mar 2022
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect EstimationStatistics in Biosciences (Stat Biosci), 2022 Kan Chen Qishuo Yin Q. Long CML 230 7 0 07 Mar 2022
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World DataSDM (SDM), 2022 Zhixuan Chu S. Rathbun Sheng Li CML OOD 120 15 0 22 Feb 2022
Evaluation Methods and Measures for Causal Learning AlgorithmsIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 204 69 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 307 33 0 02 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance Gabriel Okasa CML 173 10 0 30 Jan 2022
Deep Treatment-Adaptive Network for Causal InferenceThe VLDB journal (VLDBJ), 2021 Qian Li Zhichao Wang Shaowu Liu Gang Li Guandong Xu CML BDL OOD 107 13 0 27 Dec 2021
AI Assurance using Causal Inference: Application to Public Policy A. Svetovidov Abdul Rahman Feras A. Batarseh CML 73 2 0 01 Dec 2021
Offline Contextual Bandits for Wireless Network Optimization Miguel Suau David Lynch Alexandros Agapitos Derek Farrell M. Zhou Aleksandar Milenovic OffRL 49 4 0 11 Nov 2021
VACA: Design of Variational Graph Autoencoders for Interventional and Counterfactual Queries Pablo Sánchez-Martín Miriam Rateike Isabel Valera CML BDL 137 19 0 27 Oct 2021
GeneDisco: A Benchmark for Experimental Design in Drug DiscoveryInternational Conference on Learning Representations (ICLR), 2021 Arash Mehrjou Ashkan Soleymani Andrew Jesson Pascal Notin Y. Gal Stefan Bauer Patrick Schwab 176 25 0 22 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 295 10 0 04 Oct 2021
Estimating Categorical Counterfactuals via Deep Twin Networks Athanasios Vlontzos Bernhard Kainz Ciarán M. Gilligan-Lee OOD CML BDL 410 20 0 04 Sep 2021
Causal Effect Inference for Structured TreatmentsNeural Information Processing Systems (NeurIPS), 2021 Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 432 53 0 03 Jun 2021
Adaptive Multi-Source Causal Inference Thanh Vinh Vo Pengfei Wei T. Hoang Tze-Yun Leong 176 1 0 31 May 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments S. Parbhoo Stefan Bauer Patrick Schwab CML BDL 133 21 0 20 Mar 2021
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal InferenceAdaptive Agents and Multi-Agent Systems (AAMAS), 2021 Koh Takeuchi Ryo Nishida Hisashi Kashima Masaki Onishi CML 94 4 0 08 Feb 2021
Balance Regularized Neural Network Models for Causal Effect Estimation Mehrdad Farajtabar Andrew Lee Yuanjian Feng Vishal Gupta Peter Dolan Harish Chandran M. Szummer CML 118 7 0 23 Nov 2020
Adapting Neural Networks for Uplift Models Mouloud Belbahri Olivier Gandouet Ghaith Kazma 142 12 0 30 Oct 2020
GraphITE: Estimating Individual Effects of Graph-structured Treatments Shonosuke Harada H. Kashima CML 199 28 0 29 Sep 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 268 9 0 28 Sep 2020
Hi-CI: Deep Causal Inference in High Dimensions Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff BDL CML 230 4 0 22 Aug 2020
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution A. Khademi Vasant Honavar CML 118 9 0 01 Aug 2020
Regret Minimization for Causal Inference on Large Treatment SpaceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2020 Akira Tanimoto Tomoya Sakai Takashi Takenouchi H. Kashima CML 99 10 0 10 Jun 2020
A Survey on Causal InferenceACM Transactions on Knowledge Discovery from Data (TKDD), 2020 Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 238 591 0 05 Feb 2020
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational DataSDM (SDM), 2019 Ruocheng Guo Jundong Li Huan Liu CML OffRL 145 22 0 22 Dec 2019
Learning Individual Causal Effects from Networked Observational DataWeb Search and Data Mining (WSDM), 2019 Ruocheng Guo Wenlin Yao Huan Liu CML OOD 250 104 0 08 Jun 2019
Adapting Neural Networks for the Estimation of Treatment EffectsNeural Information Processing Systems (NeurIPS), 2019 Claudia Shi David M. Blei Victor Veitch CML 387 441 0 05 Jun 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 145 145 0 03 Feb 2019
Modified Causal Forests for Estimating Heterogeneous Causal Effects M. Lechner CML 151 52 0 22 Dec 2018