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Unifying distillation and privileged information, , , and . (2015)cite arxiv:1511.03643.Learning Disentangled Representations with Wasserstein Auto-Encoders., , and . ICLR (Workshop), OpenReview.net, (2018)Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers., , , , , , and . CVPR, page 10400-10411. IEEE, (2022)Towards Principled Disentanglement for Domain Generalization., , , , , and . CVPR, page 8014-8024. IEEE, (2022)Embrace the Gap: VAEs Perform Independent Mechanism Analysis., , , , , , , , and . NeurIPS, (2022)Interventions, Where and How? Experimental Design for Causal Models at Scale., , , , , and . NeurIPS, (2022)Exploring the Latent Space of Autoencoders with Interventional Assays., , , and . NeurIPS, (2022)Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style., , , , , , and . NeurIPS, page 16451-16467. (2021)The Inductive Bias of Quantum Kernels., , and . NeurIPS, page 12661-12673. (2021)AutoML Two-Sample Test., , , , and . NeurIPS, (2022)