Deep Structural Causal Models for Tractable Counterfactual Inference

11 June 2020

Nick Pawlowski

Daniel Coelho De Castro

Papers citing "Deep Structural Causal Models for Tractable Counterfactual Inference"

47 / 47 papers shown

Title
Causality-Driven Neural Network Repair: Challenges and Opportunities Fatemeh Vares Brittany Johnson AAML 47 0 0 24 Apr 2025
Shape Modeling of Longitudinal Medical Images: From Diffeomorphic Metric Mapping to Deep Learning Edwin Tay Nazli Tümer Amir A. Zadpoor MedIm 52 0 0 27 Mar 2025
Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE Lokesh Nagalapatti Pranava Singhal Avishek Ghosh Sunita Sarawagi CML 81 0 0 07 Feb 2025
Counterfactual Generative Modeling with Variational Causal Inference Yulun Wu Louie McConnell Claudia Iriondo CML BDL 24 0 0 16 Oct 2024
Robust image representations with counterfactual contrastive learning Mélanie Roschewitz Fabio De Sousa Ribeiro Tian Xia G. Khara Ben Glocker OOD MedIm 47 2 0 16 Sep 2024
Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations Justin Deschenaux Igor Krawczuk Grigorios G. Chrysos V. Cevher DiffM 46 3 0 29 May 2024
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models Aneesh Komanduri Chengli Zhao Feng Chen Xintao Wu CML DiffM 35 5 0 27 Apr 2024
Benchmarking Counterfactual Image Generation Thomas Melistas Nikos Spyrou Nefeli Gkouti Pedro Sanchez Athanasios Vlontzos Yannis Panagakis G. Papanastasiou Sotirios A. Tsaftaris EGVM CML 46 7 0 29 Mar 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders Christian Toth Christian Knoll Franz Pernkopf Robert Peharz CML 45 1 0 22 Feb 2024
Counterfactual Fairness for Predictions using Generative Adversarial Networks Yuchen Ma Dennis Frauen Valentyn Melnychuk Stefan Feuerriegel 31 2 0 26 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi-An Ma Rose Yu 20 4 0 10 Oct 2023
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging Charles Jones Daniel Coelho De Castro Fabio De Sousa Ribeiro Ozan Oktay Melissa McCradden Ben Glocker FaML CML 39 9 0 31 Jul 2023
MoleCLUEs: Molecular Conformers Maximally In-Distribution for Predictive Models Michael R. Maser Natasa Tagasovska Jae Hyeon Lee Andrew Watkins 31 0 0 20 Jun 2023
On Counterfactual Data Augmentation Under Confounding Abbavaram Gowtham Reddy Saketh Bachu Saloni Dash Charchit Sharma Amit Sharma V. Balasubramanian CML BDL 33 0 0 29 May 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 28 0 0 24 Mar 2023
Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities Connor Jerzak Fredrik D. Johansson Adel Daoud CML 38 11 0 30 Jan 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Biwei Huang Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 53 11 0 29 Jan 2023
Deep Causal Learning for Robotic Intelligence Y. Li CML 32 5 0 23 Dec 2022
Rethinking Causality-driven Robot Tool Segmentation with Temporal Constraints Hao Ding J. Wu Zhaoshuo Li Mathias Unberath CML 32 10 0 30 Nov 2022
Neural Bayesian Network Understudy Paloma Rabaey Cedric De Boom Thomas Demeester BDL CML 30 0 0 15 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 31 11 0 07 Nov 2022
Diffusion Visual Counterfactual Explanations Maximilian Augustin Valentyn Boreiko Francesco Croce Matthias Hein DiffM BDL 32 68 0 21 Oct 2022
Neural Causal Models for Counterfactual Identification and Estimation K. Xia Yushu Pan Elias Bareinboim CML 41 32 0 30 Sep 2022
Training Normalizing Flows from Dependent Data Matthias Kirchler C. Lippert Marius Kloft TPM 18 2 0 29 Sep 2022
Deep Structural Causal Shape Models Rajat Rasal Daniel Coelho De Castro Nick Pawlowski Ben Glocker 3DV MedIm 30 12 0 23 Aug 2022
Counterfactual Image Synthesis for Discovery of Personalized Predictive Image Markers Amar Kumar Anjun Hu Brennan Nichyporuk J. Falet Douglas L. Arnold Sotirios A. Tsaftaris Tal Arbel MedIm 19 10 0 03 Aug 2022
GLANCE: Global to Local Architecture-Neutral Concept-based Explanations Avinash Kori Ben Glocker Francesca Toni 27 6 0 05 Jul 2022
Image-based Treatment Effect Heterogeneity Connor Jerzak Fredrik D. Johansson Adel Daoud 26 20 0 13 Jun 2022
Is More Data All You Need? A Causal Exploration Athanasios Vlontzos Hadrien Reynaud Bernhard Kainz CML 19 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 30 19 0 03 Jun 2022
Causal Machine Learning for Healthcare and Precision Medicine Pedro Sanchez J. Voisey Tian Xia Hannah I. Watson Alison Q. OÑeil Sotirios A. Tsaftaris OOD CML 42 109 0 23 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 30 26 0 16 May 2022
Counterfactual harm Jonathan G. Richens R. Beard Daniel H. Thompson 23 27 0 27 Apr 2022
Feature robustness and sex differences in medical imaging: a case study in MRI-based Alzheimer's disease detection Eike Petersen Aasa Feragen Maria Luise da Costa Zemsch A. Henriksen Oskar Eiler Wiese Christensen M. Ganz OOD 16 27 0 04 Apr 2022
Explainability in reinforcement learning: perspective and position Agneza Krajna Mario Brčič T. Lipić Juraj Dončević 28 27 0 22 Mar 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 29 69 0 21 Feb 2022
A Causal Lens for Controllable Text Generation Zhiting Hu Erran L. Li 45 59 0 22 Jan 2022
Deep Causal Reasoning for Recommendations Yaochen Zhu Jing Yi Jiayi Xie Zhenzhong Chen CML BDL 22 10 0 06 Jan 2022
A Taxonomy for Inference in Causal Model Families Matej Zevcević D. Dhami Kristian Kersting 13 1 0 22 Oct 2021
Relating Graph Neural Networks to Structural Causal Models Matej Zečević D. Dhami Petar Velickovic Kristian Kersting AI4CE CML 63 53 0 09 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
Challenges for machine learning in clinical translation of big data imaging studies Nicola K. Dinsdale Emma Bluemke V. Sundaresan M. Jenkinson Stephen Smith Ana I. L. Namburete AI4CE 32 41 0 07 Jul 2021
Learning from Counterfactual Links for Link Prediction Tong Zhao Gang Liu Daheng Wang Wenhao Yu Meng-Long Jiang CML OOD 25 93 0 03 Jun 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 29 55 0 18 Mar 2021
Evaluating and Mitigating Bias in Image Classifiers: A Causal Perspective Using Counterfactuals Saloni Dash V. Balasubramanian Amit Sharma CML 27 64 0 17 Sep 2020
Explaining Visual Models by Causal Attribution Álvaro Parafita Jordi Vitrià CML FAtt 62 35 0 19 Sep 2019