from correlated data." International Conference on Machine Learning. PMLR, 2021. • Bengio, Yoshua, Aaron Courville, and Pascal Vincent. "Representation learning: A review and new perspectives." IEEE transactions on pattern analysis and machine intelligence 35.8 (2013): 1798-1828. • Kulkarni, Tejas D., et al. "Deep Convolutional Inverse Graphics Network." Advances in Neural Information Processing Systems 28 (2015): 2539-2547. • Higgins, Irina, et al. "beta-vae: Learning basic visual concepts with a constrained variational framework." (2016). • Locatello, Francesco, et al. "Challenging common assumptions in the unsupervised learning of disentangled representations." international conference on machine learning. PMLR, 2019. • Locatello, Francesco, et al. "Weakly-supervised disentanglement without compromises." International Conference on Machine Learning. PMLR, 2020. • Khemakhem, Ilyes, et al. "Variational autoencoders and nonlinear ica: A unifying framework." International Conference on Artificial Intelligence and Statistics. PMLR, 2020. 12