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Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models

1 July 2020

Papers citing "Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models"

28 / 28 papers shown

Title
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning Vahid Balazadeh Hamidreza Kamkari Valentin Thomas Benson Li Junwei Ma Jesse C. Cresswell Rahul G. Krishnan CML 24 0 0 09 Jun 2025
Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective Hechuan Wen Tong Chen Mingming Gong Li Kheng Chai S. Sadiq Hongzhi Yin CML 94 0 0 08 May 2025
Your Assumed DAG is Wrong and Here's How To Deal With It Kirtan Padh Zhufeng Li Cecilia Casolo Niki Kilbertus CML 113 0 0 24 Feb 2025
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner Valentyn Melnychuk Stefan Feuerriegel Mihaela van der Schaar CML 281 5 0 05 Nov 2024
Conformal Prediction for Causal Effects of Continuous Treatments Maresa Schröder Dennis Frauen Jonas Schweisthal Konstantin Heß Valentyn Melnychuk Stefan Feuerriegel 157 9 0 03 Jul 2024
Conformal Counterfactual Inference under Hidden Confounding Zonghao Chen Ruocheng Guo Jean-François Ton Yang Liu CML OffRL 214 3 0 20 May 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation Valentyn Melnychuk Dennis Frauen Stefan Feuerriegel CML 97 10 0 19 Nov 2023
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding Myrl G. Marmarelis Greg Ver Steeg Aram Galstyan Fred Morstatter CML OOD 97 5 0 15 Jun 2023
Reliable Off-Policy Learning for Dosage Combinations Jonas Schweisthal Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel OffRL 57 12 0 31 May 2023
Measuring axiomatic soundness of counterfactual image models M. Monteiro Fabio De Sousa Ribeiro Nick Pawlowski Daniel Coelho De Castro Ben Glocker 117 29 0 02 Mar 2023
Towards Dependable Autonomous Systems Based on Bayesian Deep Learning Components F. Arnez H. Espinoza A. Radermacher F. Terrier UQCV 70 5 0 12 Jan 2023
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
Quantifying and Using System Uncertainty in UAV Navigation F. Arnez A. Radermacher H. Espinoza BDL UQCV 65 4 0 04 Jun 2022
Predicting the impact of treatments over time with uncertainty aware neural differential equations E. Brouwer J. Hernández Stephanie L. Hyland OOD CML 55 26 0 24 Feb 2022
Selective Regression Under Fairness Criteria Abhin Shah Yuheng Bu Joshua K. Lee Subhro Das Yikang Shen P. Sattigeri G. Wornell 118 28 0 28 Oct 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 132 7 0 28 Oct 2021
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 77 15 0 11 Oct 2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks Tianhui Zhou William E Carson IV David Carlson CML 217 8 0 04 Oct 2021
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions Eoin Delaney Derek Greene Mark T. Keane 79 26 0 20 Jul 2021
Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation Ian D Kivlichan Zi Lin J. Liu Lucy Vasserman 58 20 0 09 Jul 2021
Causal Effect Inference for Structured Treatments Jean Kaddour Yuchen Zhu Qi Liu Matt J. Kusner Ricardo M. A. Silva CML 265 51 0 03 Jun 2021
Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding Andrew Jesson Sören Mindermann Y. Gal Uri Shalit CML 90 56 0 08 Mar 2021
On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty Joost R. van Amersfoort Lewis Smith Andrew Jesson Oscar Key Y. Gal UQCV 87 105 0 22 Feb 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 115 33 0 16 Feb 2021
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models Severi Rissanen Pekka Marttinen CML 183 28 0 12 Feb 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Li Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 380 1,952 0 12 Nov 2020
Targeted VAE: Variational and Targeted Learning for Causal Inference M. Vowels Necati Cihan Camgöz Richard Bowden BDL OOD CML 60 8 0 28 Sep 2020
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 283 288 0 09 Jul 2017