Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

50 / 109 papers shown

Title
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage Alexis Bellot Anish Dhir G. Prando CML 18 11 0 29 May 2022
Robust and Agnostic Learning of Conditional Distributional Treatment Effects Nathan Kallus M. Oprescu CML OOD 35 10 0 23 May 2022
An improved neural network model for treatment effect estimation Niki Kiriakidou Christos Diou CML 48 3 0 23 May 2022
Neuroevolutionary Feature Representations for Causal Inference Michael C. Burkhart Gabriel Ruiz CML OOD 21 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 32 5 0 19 May 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 10 11 0 18 Mar 2022
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials Zhixuan Chu S. Rathbun Sheng Li CML 22 10 0 10 Mar 2022
Estimating causal effects with optimization-based methods: A review and empirical comparison Martin Cousineau V. Verter S. Murphy J. Pineau CML 16 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 52 29 0 25 Feb 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 29 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 24 29 0 02 Feb 2022
A Causal Lens for Controllable Text Generation Zhiting Hu Erran L. Li 45 59 0 22 Jan 2022
BITES: Balanced Individual Treatment Effect for Survival data Stefan Schrod Andreas Schäfer S. Solbrig R. Lohmayer W. Gronwald P. Oefner T. Beissbarth Rainer Spang H. Zacharias Michael Altenbuchinger CML 15 22 0 05 Jan 2022
Causal Knowledge Guided Societal Event Forecasting Songgaojun Deng Huzefa Rangwala Yue Ning AI4TS 24 2 0 10 Dec 2021
Enhancing Counterfactual Classification via Self-Training Ruijiang Gao Max Biggs Wei-Ju Sun Ligong Han CML OffRL 32 6 0 08 Dec 2021
Loss Functions for Discrete Contextual Pricing with Observational Data Max Biggs Ruijiang Gao Wei-Ju Sun 31 10 0 18 Nov 2021
Interpretable Personalized Experimentation Han Wu S. Tan Weiwei Li Mia Garrard Adam Obeng Drew Dimmery Shaun Singh Hanson Wang Daniel R. Jiang E. Bakshy 25 5 0 05 Nov 2021
Cycle-Balanced Representation Learning For Counterfactual Inference Guanglin Zhou L. Yao Xiwei Xu Chen Wang Liming Zhu CML OOD 14 12 0 29 Oct 2021
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game Yuzi He Christopher Tran Julie Jiang Keith Burghardt Emilio Ferrara Elena Zheleva Kristina Lerman 19 10 0 27 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 27 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 14 17 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
The Bias-Variance Tradeoff of Doubly Robust Estimator with Targeted $L_1$ regularized Neural Networks Predictions M. Rostami O. Saarela M. Escobar 40 1 0 02 Aug 2021
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition Junkun Yuan Anpeng Wu Kun Kuang Yangqiu Song Runze Wu Fei Wu Lanfen Lin CML 42 38 0 13 Jul 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 36 12 0 22 Jun 2021
Learning from Counterfactual Links for Link Prediction Tong Zhao Gang Liu Daheng Wang Wenhao Yu Meng Jiang CML OOD 28 93 0 03 Jun 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments S. Parbhoo Stefan Bauer Patrick Schwab CML BDL 11 16 0 20 Mar 2021
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments Lizhen Nie Mao Ye Qiang Liu D. Nicolae CML 17 68 0 14 Mar 2021
Limitations of Post-Hoc Feature Alignment for Robustness Collin Burns Jacob Steinhardt OOD 14 22 0 10 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 35 108 0 08 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
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners E. C. Neto OOD CML 24 6 0 09 Nov 2020
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review A. Caron G. Baio I. Manolopoulou CML 28 52 0 14 Sep 2020
Estimating Individual Treatment Effects with Time-Varying Confounders Ruoqi Liu Changchang Yin Ping Zhang CML 26 27 0 27 Aug 2020
On Learning Language-Invariant Representations for Universal Machine Translation Hao Zhao Junjie Hu Andrej Risteski 40 11 0 11 Aug 2020
Learning Decomposed Representation for Counterfactual Inference Anpeng Wu Kun Kuang Junkun Yuan Bo Li Jianrong Tao Qiang Zhu Yueting Zhuang Fei Wu CML 21 21 0 12 Jun 2020
CausaLM: Causal Model Explanation Through Counterfactual Language Models Amir Feder Nadav Oved Uri Shalit Roi Reichart CML LRM 36 156 0 27 May 2020
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks Ioana Bica James Jordon M. Schaar CML 22 105 0 27 Feb 2020
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models Imke Mayer Julie Josse Félix Raimundo Jean-Philippe Vert CML 24 12 0 25 Feb 2020
Causal Inference under Networked Interference and Intervention Policy Enhancement Yunpu Ma Volker Tresp CML 31 40 0 20 Feb 2020
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations Ioana Bica Ahmed Alaa James Jordon M. Schaar BDL CML 11 179 0 10 Feb 2020
Artificial Intelligence for Social Good: A Survey Zheyuan Ryan Shi Claire Wang Fei Fang AI4TS 32 81 0 07 Jan 2020
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data Ruocheng Guo Jundong Li Huan Liu CML OffRL 25 21 0 22 Dec 2019
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 34 19 0 25 Jun 2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models Michael Oberst David Sontag CML OffRL 13 168 0 14 May 2019
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines Chirag Nagpal Dennis L. Wei B. Vinzamuri Monica Shekhar Sara E. Berger Subhro Das Kush R. Varshney CML 6 25 0 08 May 2019
Classifying Treatment Responders Under Causal Effect Monotonicity Nathan Kallus CML 23 16 0 14 Feb 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 46 332 0 30 Jan 2019
Adversarial Balancing for Causal Inference Michal Ozery-Flato Pierre Thodoroff Matan Ninio Michal Rosen-Zvi T. El-Hay CML GAN 8 25 0 17 Oct 2018