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Sound and complete algorithms have been proposed to compute identifiable causal queries using the causal structure and data.
[bayesian analysis in expert systems]: comment: graphical models, causality and intervention
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Tian, J. and Pearl, J · 2002
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A characterization of interventional distributions in semi-markovian causal models
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What counterfactuals can be tested
Shpitser, I. and Pearl, J · 2007
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Complete identification methods for the causal hierarchy
Shpitser, I. and Pearl, J · 2008
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Causality
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Pearl’s calculus of intervention is complete
Huang, Y. and Valtorta, M · 2012
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Conditional generative adversarial nets
Mirza, M. and Osindero, S · 2014
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Improved training of wasserstein gans
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Causal effect inference with deep latent-variable models
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Shalit, U., Johansson, F. D., and Sontag, D · 2017
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Causalgan: Learning causal implicit generative models with adversarial training
Kocaoglu, M., Snyder, C., Dimakis, A. G., and Vishwanath, S · 2018
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Invariant risk minimization
Arjovsky, M., Bottou, L., Gulrajani, I., and Lopez-Paz, D · 2019
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Causal identification under markov equivalence: Completeness results
Jaber, A., Zhang, J., and Bareinboim, E · 2019
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A style-based generator architecture for generative adversarial networks
Karras, T., Laine, S., and Aila, T · 2019
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Preventing failures due to dataset shift: Learning predictive models that transport
Subbaswamy, A., Schulam, P., and Saria, S · 2019
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Achieving causal fairness through generative adversarial networks
Xu, D., Wu, Y., Yuan, S., Zhang, L., and Wu, X · 2019
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Estimating the effects of continuous-valued interventions using generative adversarial networks
Bica, I., Jordon, J., and van der Schaar, M · 2020
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Causality matters in medical imaging
Castro, D. C., Walker, I., and Glocker, B · 2020
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Maskgan: Towards diverse and interactive facial image manipulation
Lee, C.-H., Liu, Z., Wu, L., and Luo, P · 2020
Treatment effect estimation with disentangled latent factors
Zhang, W., Liu, L., and Li, J · 2021
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Partial identification of treatment effects with implicit generative models
Balazadeh Meresht, V., Syrgkanis, V., and Krishnan, R. G · 2022
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Evaluating and mitigating bias in image classifiers: A causal perspective using counterfactuals
Dash, S., Balasubramanian, V. N., and Sharma, A · 2022
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Causal inference in recommender systems: A survey and future directions
Gao, C., Zheng, Y., Wang, W., Feng, F., He, X., and Li, Y · 2022
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Classifier-free diffusion guidance
Ho, J. and Salimans, T · 2022
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Countergan: generating realistic counterfactuals with residual generative adversarial nets
Nemirovsky, D., Thiebaut, N., Xu, Y., and Gupta, A · 2020
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Deep structural causal models for tractable counterfactual inference
Pawlowski, N., Coelho de Castro, D., and Glocker, B · 2020
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pytorch-fid: FID Score for PyTorch
Seitzer, M · 2020
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Interpreting the latent space of gans for semantic face editing
Shen, Y., Gu, J., Tang, X., and Zhou, B · 2020
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Denoising diffusion implicit models
Song, J., Meng, C., and Ermon, S · 2020
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Causal interventional training for image recognition
Qin, W., Zhang, H., Hong, R., Lim, E.-P., and Sun, Q · 2021
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Jerzak, C. T., Johansson, F., and Daoud, A · 2022
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An adaptive kernel approach to federated learning of heterogeneous causal effects
Vo, T. V., Bhattacharyya, A., Lee, Y., and Leong, T.-Y · 2022
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Continually updating neural causal models
Busch, F. P., Seng, J., Willig, M., and Zečević, M · 2023
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Interventional and counterfactual inference with diffusion models
Chao, P., Blöbaum, P., and Kasiviswanathan, S. P · 2023
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Cxr-acgan: Auxiliary classifier gan (ac-gan) for conditional generation of chest x-ray images (pneumonia, covid-19 and healthy patients) for the purpose of data augmentation
Giorgio Carbone, Remo Marconzini, G. C · 2023
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Finding invariant predictors efficiently via causal structure
Lee, K., Rahman, M. M., and Kocaoglu, M · 2023
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Measuring axiomatic soundness of counterfactual image models
Monteiro, M., Ribeiro, F. D. S., Pawlowski, N., Castro, D. C., and Glocker, B · 2023
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High fidelity image counterfactuals with probabilistic causal models
Ribeiro, F. D. S., Xia, T., Monteiro, M., Pawlowski, N., and Glocker, B · 2023
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Neural causal models for counterfactual identification and estimation
Xia, K. M., Pan, Y., and Bareinboim, E · 2023
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Covid-net: a tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images
Wang, L., Lin, Z. Q., and Wong, A · 2045
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