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From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling

17 October 2023

Papers citing "From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling"

50 / 51 papers shown

Title
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 268 22 0 28 Feb 2024
High Fidelity Image Counterfactuals with Probabilistic Causal Models Fabio De Sousa Ribeiro Tian Xia M. Monteiro Nick Pawlowski Ben Glocker DiffM 80 39 0 27 Jun 2023
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms Aneesh Komanduri Yongkai Wu Feng Chen Xintao Wu CML OOD 66 10 0 02 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 125 64 0 01 Jun 2023
Measuring axiomatic soundness of counterfactual image models M. Monteiro Fabio De Sousa Ribeiro Nick Pawlowski Daniel Coelho De Castro Ben Glocker 106 29 0 02 Mar 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Erdun Gao Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 119 11 0 29 Jan 2023
Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger Luigi Gresele Jack Brady Julius von Kügelgen Dominik Zietlow Bernhard Schölkopf Georg Martius Wieland Brendel M. Besserve DRL 68 20 0 06 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 82 119 0 23 May 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 69 46 0 01 Apr 2022
Weakly supervised causal representation learning Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 88 131 0 30 Mar 2022
Diffusion Models for Counterfactual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 110 58 0 29 Mar 2022
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 85 75 0 21 Feb 2022
Privacy-preserving Generative Framework Against Membership Inference Attacks Ruikang Yang Jianfeng Ma Yinbin Miao Xindi Ma 44 5 0 11 Feb 2022
A Style and Semantic Memory Mechanism for Domain Generalization Yang Chen Yu Wang Yingwei Pan Ting Yao Xinmei Tian Tao Mei 60 42 0 14 Dec 2021
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation Konpat Preechakul Nattanat Chatthee Suttisak Wizadwongsa Supasorn Suwajanakorn SyDa DiffM 121 434 0 30 Nov 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 58 84 0 08 Sep 2021
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 57 72 0 22 Jul 2021
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sébastien Lachapelle Pau Rodríguez López Yash Sharma Katie Everett Rémi Le Priol Alexandre Lacoste Simon Lacoste-Julien CML OOD 90 140 0 21 Jul 2021
Exploring the Latent Space of Autoencoders with Interventional Assays Felix Leeb Stefan Bauer M. Besserve Bernhard Schölkopf DRL 80 18 0 30 Jun 2021
Independent mechanism analysis, a new concept? Luigi Gresele Julius von Kügelgen Vincent Stimper Bernhard Schölkopf M. Besserve CML 68 102 0 09 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen Yash Sharma Luigi Gresele Wieland Brendel Bernhard Schölkopf M. Besserve Francesco Locatello 99 317 0 08 Jun 2021
Diffusion-Based Representation Learning K. Abstreiter Sarthak Mittal Stefan Bauer Bernhard Schölkopf Arash Mehrjou DiffM 77 58 0 29 May 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 265 7,938 0 11 May 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 115 303 0 03 Mar 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 353 6,566 0 26 Nov 2020
Causal Autoregressive Flows Ilyes Khemakhem R. Monti R. Leech Aapo Hyvarinen CML OOD AI4CE 83 110 0 04 Nov 2020
Denoising Diffusion Implicit Models Jiaming Song Chenlin Meng Stefano Ermon VLM DiffM 289 7,469 0 06 Oct 2020
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators Dingfan Chen Tribhuvanesh Orekondy Mario Fritz SyDa 56 185 0 15 Jun 2020
Domain Generalization using Causal Matching Divyat Mahajan Shruti Tople Amit Sharma OOD 89 337 0 12 Jun 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 242 320 0 07 Feb 2020
DP-CGAN: Differentially Private Synthetic Data and Label Generation Reihaneh Torkzadehmahani Peter Kairouz B. Paten SyDa 72 238 0 27 Jan 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 209 1,713 0 05 Dec 2019
Masked Gradient-Based Causal Structure Learning Ignavier Ng Shengyu Zhu Zhuangyan Fang Haoyang Li Zhitang Chen Jun Wang CML 119 117 0 18 Oct 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 195 2,242 0 05 Jul 2019
On the Transfer of Inductive Bias from Simulation to the Real World: a New Disentanglement Dataset Muhammad Waleed Gondal Manuel Wüthrich Ðorðe Miladinovic Francesco Locatello M. Breidt V. Volchkov J. Akpo Olivier Bachem Bernhard Schölkopf Stefan Bauer OOD DRL 102 138 0 07 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 73 227 0 31 May 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 82 489 0 22 Apr 2019
Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst Dhruv Batra Devi Parikh Stefan Lee CML 80 512 0 16 Apr 2019
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 133 162 0 31 Oct 2018
FairGAN: Fairness-aware Generative Adversarial Networks Depeng Xu Shuhan Yuan Lu Zhang Xintao Wu GAN 111 315 0 28 May 2018
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 97 331 0 22 May 2018
Differentially Private Generative Adversarial Network Liyang Xie Kaixiang Lin Shu Wang Fei Wang Jiayu Zhou SyDa 92 501 0 19 Feb 2018
Disentangling by Factorising Hyunjik Kim A. Mnih CoGe OOD 64 1,356 0 16 Feb 2018
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training Murat Kocaoglu Christopher Snyder A. Dimakis S. Vishwanath GAN OOD 84 256 0 06 Sep 2017
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations Diane Bouchacourt Ryota Tomioka Sebastian Nowozin BDL OOD DRL 56 314 0 24 May 2017
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 216 6,162 0 01 Jul 2016
The Variational Fair Autoencoder Christos Louizos Kevin Swersky Yujia Li Max Welling R. Zemel DRL 223 636 0 03 Nov 2015
Deep Unsupervised Learning using Nonequilibrium Thermodynamics Jascha Narain Sohl-Dickstein Eric A. Weiss Niru Maheswaranathan Surya Ganguli SyDa DiffM 306 7,016 0 12 Mar 2015
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 247 8,426 0 28 Nov 2014
On Causal and Anticausal Learning Bernhard Schölkopf Dominik Janzing J. Peters Eleni Sgouritsa Kun Zhang Joris Mooij CML 94 612 0 27 Jun 2012