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Maja Rudolph

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Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior

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May 22, 2024
Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu

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On the Challenges and Opportunities in Generative AI

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Feb 28, 2024
Laura Manduchi, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

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Towards Fast Stochastic Sampling in Diffusion Generative Models

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Feb 13, 2024
Kushagra Pandey, Maja Rudolph, Stephan Mandt

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Hybrid Modeling Design Patterns

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Dec 29, 2023
Maja Rudolph, Stefan Kurz, Barbara Rakitsch

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Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data

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Oct 16, 2023
Clement Fung, Chen Qiu, Aodong Li, Maja Rudolph

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Efficient Integrators for Diffusion Generative Models

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Oct 11, 2023
Kushagra Pandey, Maja Rudolph, Stephan Mandt

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LoRA ensembles for large language model fine-tuning

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Oct 04, 2023
Xi Wang, Laurence Aitchison, Maja Rudolph

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Deep Anomaly Detection on Tennessee Eastman Process Data

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Mar 10, 2023
Fabian Hartung, Billy Joe Franks, Tobias Michels, Dennis Wagner, Philipp Liznerski, Steffen Reithermann, Sophie Fellenz, Fabian Jirasek, Maja Rudolph, Daniel Neider, Heike Leitte, Chen Song, Benjamin Kloepper, Stephan Mandt, Michael Bortz, Jakob Burger, Hans Hasse, Marius Kloft

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Deep Anomaly Detection under Labeling Budget Constraints

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Feb 15, 2023
Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph

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Zero-Shot Anomaly Detection without Foundation Models

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Feb 15, 2023
Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

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