Burg, Max, et al. “Image Retrieval Outperforms Diffusion Models on Data Augmentation.” Journal of Machine Learning Research, ML Research Press, 2023.
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Yao, Dingling, et al. “Multi-View Causal Representation Learning with Partial Observability.”10.48550/arXiv.2311.04056__ArXiv, 2311.04056, doi:10.48550/arXiv.2311.04056.
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arXiv: 2311.04056

Maiorca, Valentino, et al. “Latent Space Translation via Semantic Alignment.”10.48550/arXiv.2311.00664__ArXiv, 2311.00664, doi:10.48550/arXiv.2311.00664.
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arXiv: 2311.00664

Kori, Avinash, et al. “Grounded Object Centric Learning.”10.48550/arXiv.2307.09437__ArXiv, 2307.09437, doi:10.48550/arXiv.2307.09437.
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arXiv: 2307.09437

Zhu, Zhenyu, et al. “Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling.”10.48550/arXiv.2310.18123__ArXiv, 2310.18123, doi:10.48550/arXiv.2310.18123.
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arXiv: 2310.18123

Montagna, Francesco, et al. “Assumption Violations in Causal Discovery and the Robustness of Score Matching.”10.48550/arXiv.2310.13387__ArXiv, 2310.13387, doi:10.48550/arXiv.2310.13387.
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arXiv: 2310.13387

Fumero, Marco, et al. “Leveraging Sparse and Shared Feature Activations for Disentangled Representation Learning.”10.48550/arXiv.2304.07939__ArXiv, 2304.07939, doi:10.48550/arXiv.2304.07939.
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arXiv: 2304.07939

Löwe, Sindy, et al. “Rotating Features for Object Discovery.”10.48550/arXiv.2306.00600__ArXiv, 2306.00600, doi:10.48550/arXiv.2306.00600.
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arXiv: 2306.00600

Montagna, Francesco, et al. “Shortcuts for Causal Discovery of Nonlinear Models by Score Matching.”10.48550/arXiv.2310.14246__ArXiv, 2310.14246, doi:10.48550/arXiv.2310.14246.
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arXiv: 2310.14246

Xu, Danru, et al. “A Sparsity Principle for Partially Observable Causal Representation Learning.” Causal Representation Learning Workshop at NeurIPS 2023, 54, OpenReview, 2023.
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Fu, Teng, et al. “Mismatched Estimation of Non-Symmetric Rank-One Matrices Corrupted by Structured Noise.”10.1109/isit54713.2023.10206671__Proceedings of 2023 IEEE International Symposium on Information Theory, IEEE, doi:10.1109/isit54713.2023.10206671.
LibreCat: https://research-explorer.ista.ac.at/record/14923
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arXiv: 2302.03306

Marensi, Elena, et al. “Dynamics and Proliferation of Turbulent Stripes in Plane-Poiseuille and Plane-Couette Flows.”10.1017/jfm.2023.780__Journal of Fluid Mechanics, vol. 974, , Cambridge University Press, 2023, doi:10.1017/jfm.2023.780.
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arXiv: 2212.12406

Jethwa, Rajesh B., et al. “To DISP or Not? The Farreaching Reaction Mechanisms Underpinning Lithiumair Batteries.”10.1002/anie.202316476__Angewandte Chemie International Edition, e202316476, Wiley, 2023, doi:10.1002/anie.202316476.
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Liu, Zhengtao, et al. “Lattice Expansion Enables Interstitial Doping to Achieve a High Average ZT in Ntype PbS.”10.1002/idm2.12056__Interdisciplinary Materials, vol. 2, no. 1, Wiley, 2023, pp. 161–70, doi:10.1002/idm2.12056.
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Malvai, Harjasleen, et al. “Parakeet: Practical Key Transparency for End-to-End EEncrypted Messaging.”10.14722/ndss.2023.24545__Proceedings of the 2023 Network and Distributed System Security Symposium, Internet Society, 2023, doi:10.14722/ndss.2023.24545.
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Benes, Nikola, et al. “Phenotype Control of Partially Specified Boolean Networks.”10.1007/978-3-031-42697-1_2__21st International Conference on Computational Methods in Systems Biology, vol. 14137, Springer Nature, 2023, pp. 18–35, doi:10.1007/978-3-031-42697-1_2.
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Lewin, Mathieu, et al. “Universal Functionals in Density Functional Theory.”10.1007/978-3-031-22340-2_3__Density Functional Theory, edited by Eric Cances and Gero Friesecke, 1st ed., Springer, 2023, pp. 115–82, doi:10.1007/978-3-031-22340-2_3.
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arXiv: 1912.10424

Becker, Lea Marie, et al. “The Rigid Core and Flexible Surface of Amyloid Fibrils Probed by MagicAngle Spinning NMR of Aromatic Residues.”10.1002/anie.202219314__Angewandte Chemie International Edition, vol. 62, no. 19, e202219314, Wiley, 2023, doi:10.1002/anie.202219314.
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Becker, Lea Marie, and Paul Schanda. Research Data to: The Rigid Core and Flexible Surface of Amyloid Fibrils Probed by Magic-Angle-Spinning NMR Spectroscopy of Aromatic Residues. Institute of Science and Technology Austria, 2023, doi:10.15479/AT:ISTA:12497.
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DOI: 10.15479/AT:ISTA:12497

Danzl, Johann G. Research Data for the Publication “Imaging Brain Tissue Architecture across Millimeter to Nanometer Scales.” Institute of Science and Technology Austria, 2023, doi:10.15479/AT:ISTA:13126.
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