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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 403 papers shown

Title
Data-Driven Offline Decision-Making via Invariant Representation Learning Qi Yi-Hsun Su Aviral Kumar Sergey Levine OffRL 91 22 0 21 Nov 2022
Counterfactual Learning with Multioutput Deep Kernels A. Caron G. Baio I. Manolopoulou BDL CML OffRL 72 1 0 20 Nov 2022
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Leilei Gan CML 81 0 0 18 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 119 11 0 07 Nov 2022
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation Diego Martinez-Taboada Dino Sejdinovic CML OffRL 43 0 0 02 Nov 2022
Inference and Denoise: Causal Inference-based Neural Speech Enhancement Tsun-An Hsieh Chao-Han Huck Yang Pin-Yu Chen Sabato Marco Siniscalchi Yu Tsao CML 83 2 0 02 Nov 2022
Robust Direct Learning for Causal Data Fusion Xinyu Li Yilin Li Daixin Wang Longfei Li Jun Zhou CML 47 1 0 01 Nov 2022
Learning Individual Treatment Effects under Heterogeneous Interference in Networks Ziyu Zhao Yuqi Bai Kun Kuang Ruoxuan Xiong Leilei Gan CML 65 8 0 25 Oct 2022
Adversarial De-confounding in Individualised Treatment Effects Estimation Vinod Kumar Chauhan Soheila Molaei Marzia Hoque Tania Anshul Thakur T. Zhu David Clifton CML 46 14 0 19 Oct 2022
Deep Counterfactual Estimation with Categorical Background Variables E. Brouwer CML 110 7 0 11 Oct 2022
Transfer Learning for Individual Treatment Effect Estimation Ahmed Aloui Juncheng Dong Cat P. Le Vahid Tarokh CML 116 2 0 01 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 100 39 0 30 Sep 2022
Weather2vec: Representation Learning for Causal Inference with Non-Local Confounding in Air Pollution and Climate Studies M. Tec James G. Scott Corwin M. Zigler CML 44 12 0 25 Sep 2022
A Survey of Deep Causal Models and Their Industrial Applications Zongyu Li Xiaoning Guo Siwei Qiang CML AI4CE 76 8 0 19 Sep 2022
Semi-supervised Batch Learning From Logged Data Gholamali Aminian Armin Behnamnia R. Vega Laura Toni Chengchun Shi Hamid R. Rabiee Omar Rivasplata Miguel R. D. Rodrigues OffRL 53 1 0 15 Sep 2022
Normalizing Flows for Interventional Density Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel 99 21 0 13 Sep 2022
Moderately-Balanced Representation Learning for Treatment Effects with Orthogonality Information Yiyan Huang Cheuk Hang Leung Shumin Ma Qi Wu DongDong Wang Zhixiang Huang OOD CML 59 3 0 05 Sep 2022
Deep Stable Representation Learning on Electronic Health Records Yingtao Luo Zhaocheng Liu Qiang Liu OOD BDL CML 79 3 0 03 Sep 2022
Learning to Infer Counterfactuals: Meta-Learning for Estimating Multiple Imbalanced Treatment Effects Guanglin Zhou Lina Yao Xiwei Xu Chen Wang Liming Zhu OOD CML BDL 57 2 0 13 Aug 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
DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation Kailiang Zhong Fengtong Xiao Yan Ren Yaorong Liang Wenqing Yao Xiaofeng Yang Ling Cen CML 52 21 0 19 Jul 2022
Device-Cloud Collaborative Recommendation via Meta Controller Jiangchao Yao Feng Wang Xichen Ding Shaohu Chen Bo Han Jingren Zhou Hongxia Yang 102 18 0 07 Jul 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty Christopher Tran Elena Zheleva CML 68 4 0 25 Jun 2022
Interpretable Deep Causal Learning for Moderation Effects A. Caron G. Baio I. Manolopoulou CML OOD 50 2 0 21 Jun 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
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
Adversarial Counterfactual Environment Model Learning Xiong-Hui Chen Yang Yu Zhenghong Zhu Zhihua Yu Zhen-Yu Chen ... Yinan Wu Hongqiu Wu Rongjun Qin Rui Ding Fangsheng Huang CML OffRL 88 12 0 10 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 63 2 0 06 Jun 2022
Estimating counterfactual treatment outcomes over time in complex multiagent scenarios Keisuke Fujii Koh Takeuchi Atsushi Kuribayashi Naoya Takeishi Yoshinobu Kawahara K. Takeda CML 71 15 0 04 Jun 2022
Learning Disentangled Representations for Counterfactual Regression via Mutual Information Minimization Min Cheng Xinru Liao Quanlian Liu Bin Ma Jian Xu Bo Zheng CML 69 25 0 02 Jun 2022
Feature Selection for Discovering Distributional Treatment Effect Modifiers Yoichi Chikahara M. Yamada H. Kashima CML 51 5 0 01 Jun 2022
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects Naoufal Acharki Ramiro Lugo A. Bertoncello Josselin Garnier CML 70 13 0 29 May 2022
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage Alexis Bellot Anish Dhir G. Prando CML 58 11 0 29 May 2022
An improved neural network model for treatment effect estimation Niki Kiriakidou Christos Diou CML 87 3 0 23 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus Miruna Oprescu OOD CML 122 12 0 23 May 2022
Neuroevolutionary Feature Representations for Causal Inference Michael C. Burkhart Gabriel Ruiz CML OOD 44 2 0 21 May 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
Causal Transformer for Estimating Counterfactual Outcomes Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 107 99 0 14 Apr 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 75 11 0 18 Mar 2022
Undersmoothing Causal Estimators with Generative Trees Damian Machlanski Spyridon Samothrakis Paul Clarke CML 96 1 0 16 Mar 2022
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials Zhixuan Chu S. Rathbun Sheng Li CML 49 10 0 10 Mar 2022
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation Kan Chen Qishuo Yin Q. Long CML 68 5 0 07 Mar 2022
Estimating Conditional Average Treatment Effects with Missing Treatment Information Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 50 6 0 02 Mar 2022
Neural Score Matching for High-Dimensional Causal Inference Oscar Clivio Fabian Falck B. Lehmann George Deligiannidis Chris Holmes CML 66 8 0 01 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter Susan Murphy J. Pineau CML 40 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 90 32 0 25 Feb 2022
Ensemble Method for Estimating Individualized Treatment Effects K. Han Hanghao Wu CML FedML 27 4 0 25 Feb 2022
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data Zhixuan Chu S. Rathbun Sheng Li CML OOD 83 15 0 22 Feb 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 99 76 0 21 Feb 2022
Hierarchical Interpretation of Neural Text Classification Hanqi Yan Lin Gui Yulan He 105 14 0 20 Feb 2022