Kloft, Marius

63 publications

TMLR 2025 Explaining Bayesian Neural Networks Kirill Bykov, Marina MC Höhne, Adelaida Creosteanu, Klaus Robert Muller, Frederick Klauschen, Shinichi Nakajima, Marius Kloft

NeurIPS 2025 Mitigating Spurious Features in Contrastive Learning with Spectral Regularization Naghmeh Ghanooni, Waleed Mustafa, Dennis Wagner, Sophie Fellenz, Anthony Widjaja Lin, Marius Kloft

NeurIPS 2025 NoBOOM: Chemical Process Datasets for Industrial Anomaly Detection Dennis Wagner, Fabian Hartung, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Arjun Nair, Steffen Reithermann, Ralf Schulz, Michael Bortz, Daniel Neider, Heike Leitte, Joachim Pfeffinger, Stephan Mandt, Sophie Fellenz, Torsten Katz, Fabian Jirasek, Jakob Burger, Hans Hasse, Marius Kloft

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, 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

TMLR 2025 Towards Graph Foundation Models: A Study on the Generalization of Positional and Structural Encodings Billy Joe Franks, Moshe Eliasof, Semih Cantürk, Guy Wolf, Carola-Bibiane Schönlieb, Sophie Fellenz, Marius Kloft

ICMLW 2024 Comgra: A Tool for Analyzing and Debugging Neural Networks Florian Dietz, Sophie Fellenz, Dietrich Klakow, Marius Kloft

TMLR 2024 Generalization Bounds with Logarithmic Negative-Sample Dependence for Adversarial Contrastive Learning Naghmeh Ghanooni, Waleed Mustafa, Yunwen Lei, Anthony Widjaja Lin, Marius Kloft

IJCAI 2024 Interpretable Tensor Fusion Saurabh Varshneya, Antoine Ledent, Philipp Liznerski, Andriy Balinskyy, Purvanshi Mehta, Waleed Mustafa, Marius Kloft

AISTATS 2024 Non-Vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks Waleed Mustafa, Philipp Liznerski, Antoine Ledent, Dennis Wagner, Puyu Wang, Marius Kloft

TMLR 2023 A Systematic Approach to Universal Random Features in Graph Neural Networks Billy Joe Franks, Markus Anders, Marius Kloft, Pascal Schweitzer

ICML 2023 Deep Anomaly Detection Under Labeling Budget Constraints Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph

AAAI 2023 Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings Antoine Ledent, Rodrigo Alves, Yunwen Lei, Yann Guermeur, Marius Kloft

NeurIPS 2023 Labeling Neural Representations with Inverse Recognition Kirill Bykov, Laura Kopf, Shinichi Nakajima, Marius Kloft, Marina Höhne

ECML-PKDD 2023 Ordinal Regression for Difficulty Prediction of StepMania Levels Billy Joe Franks, Benjamin Dinkelmann, Marius Kloft, Sophie Fellenz

TMLR 2023 TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection Dennis Wagner, Tobias Michels, Florian C.F. Schulz, Arjun Nair, Maja Rudolph, Marius Kloft

ICML 2023 Training Normalizing Flows from Dependent Data Matthias Kirchler, Christoph Lippert, Marius Kloft

NeurIPS 2023 Zero-Shot Anomaly Detection via Batch Normalization Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

TMLR 2022 Exposing Outlier Exposure: What Can Be Learned from Few, One, and Zero Outlier Images Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus Robert Muller, Marius Kloft

ICML 2022 Latent Outlier Exposure for Anomaly Detection with Contaminated Data Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt

ICML 2022 On the Generalization Analysis of Adversarial Learning Waleed Mustafa, Yunwen Lei, Marius Kloft

IJCAI 2022 Raising the Bar in Graph-Level Anomaly Detection Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

NeurIPSW 2022 Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings. Ajay Chawda, Stefanie Grimm, Marius Kloft

ICLR 2021 Explainable Deep One-Class Classification Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Marius Kloft, Klaus Robert Muller

NeurIPS 2021 Fine-Grained Generalization Analysis of Inductive Matrix Completion Antoine Ledent, Rodrigo Alves, Yunwen Lei, Marius Kloft

IJCAI 2021 Fine-Grained Generalization Analysis of Structured Output Prediction Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft

AAAI 2021 Fine-Grained Generalization Analysis of Vector-Valued Learning Liang Wu, Antoine Ledent, Yunwen Lei, Marius Kloft

IJCAI 2021 Learning Interpretable Concept Groups in CNNs Saurabh Varshneya, Antoine Ledent, Robert A. Vandermeulen, Yunwen Lei, Matthias Enders, Damian Borth, Marius Kloft

AAAI 2021 Model Uncertainty Guides Visual Object Tracking Lijun Zhou, Antoine Ledent, Qintao Hu, Ting Liu, Jianlin Zhang, Marius Kloft

ICML 2021 Neural Transformation Learning for Deep Anomaly Detection Beyond Images Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph

AAAI 2021 Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks Antoine Ledent, Waleed Mustafa, Yunwen Lei, Marius Kloft

ICLR 2020 Deep Semi-Supervised Anomaly Detection Lukas Ruff, Robert A. Vandermeulen, Nico Görnitz, Alexander Binder, Emmanuel Müller, Klaus-Robert Müller, Marius Kloft

NeurIPS 2020 Sharper Generalization Bounds for Pairwise Learning Yunwen Lei, Antoine Ledent, Marius Kloft

AISTATS 2020 Two-Sample Testing Using Deep Learning Matthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert

NeurIPS 2019 Effective End-to-End Unsupervised Outlier Detection via Inlier Priority of Discriminative Network Siqi Wang, Yijie Zeng, Xinwang Liu, En Zhu, Jianping Yin, Chuanfu Xu, Marius Kloft

AAAI 2019 Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation Florian Wenzel, Théo Galy-Fajou, Christian Donner, Marius Kloft, Manfred Opper

ICML 2018 Deep One-Class Classification Lukas Ruff, Robert Vandermeulen, Nico Goernitz, Lucas Deecke, Shoaib Ahmed Siddiqui, Alexander Binder, Emmanuel Müller, Marius Kloft

ECML-PKDD 2018 Image Anomaly Detection with Generative Adversarial Networks Lucas Deecke, Robert A. Vandermeulen, Lukas Ruff, Stephan Mandt, Marius Kloft

JMLR 2018 Local Rademacher Complexity-Based Learning Guarantees for Multi-Task Learning Niloofar Yousefi, Yunwen Lei, Marius Kloft, Mansooreh Mollaghasemi, Georgios C. Anagnostopoulos

AISTATS 2018 Scalable Generalized Dynamic Topic Models Patrick Jähnichen, Florian Wenzel, Marius Kloft, Stephan Mandt

ECML-PKDD 2017 Bayesian Nonlinear Support Vector Machines for Big Data Florian Wenzel, Théo Galy-Fajou, Matthäus Deutsch, Marius Kloft

MLJ 2017 Sparse Probit Linear Mixed Model Stephan Mandt, Florian Wenzel, Shinichi Nakajima, John P. Cunningham, Christoph Lippert, Marius Kloft

ECML-PKDD 2016 Huber-Norm Regularization for Linear Prediction Models Oleksandr Zadorozhnyi, Gunthard Benecke, Stephan Mandt, Tobias Scheffer, Marius Kloft

ACML 2016 Localized Multiple Kernel Learning—A Convex Approach Yunwen Lei, Alexander Binder, Urun Dogan, Marius Kloft

UAI 2016 Separating Sparse Signals from Correlated Noise in Binary Classification Stephan Mandt, Florian Wenzel, Shinichi Nakajima, Christoph Lippert, Marius Kloft

ICML 2015 Hidden Markov Anomaly Detection Nico Goernitz, Mikio Braun, Marius Kloft

NeurIPS 2015 Multi-Class SVMs: From Tighter Data-Dependent Generalization Bounds to Novel Algorithms Yunwen Lei, Urun Dogan, Alexander Binder, Marius Kloft

ECML-PKDD 2015 Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms Marina M.-C. Vidovic, Nico Görnitz, Klaus-Robert Müller, Gunnar Rätsch, Marius Kloft

MLJ 2015 Probabilistic Clustering of Time-Evolving Distance Data Julia E. Vogt, Marius Kloft, Stefan Stark, Sudhir Raman, Sandhya Prabhakaran, Volker Roth, Gunnar Rätsch

AISTATS 2014 Learning and Evaluation in Presence of Non-I.i.d. Label Noise Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft

COLT 2014 Localized Complexities for Transductive Learning Ilya O. Tolstikhin, Gilles Blanchard, Marius Kloft

NeurIPS 2013 Learning Kernels Using Local Rademacher Complexity Corinna Cortes, Marius Kloft, Mehryar Mohri

JAIR 2013 Toward Supervised Anomaly Detection Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf Brefeld

ECML-PKDD 2012 Efficient Training of Graph-Regularized Multitask SVMs Christian Widmer, Marius Kloft, Nico Görnitz, Gunnar Rätsch

JMLR 2012 On the Convergence Rate of Lp-Norm Multiple Kernel Learning Marius Kloft, Gilles Blanchard

JMLR 2012 Security Analysis of Online Centroid Anomaly Detection Marius Kloft, Pavel Laskov

JMLR 2011 Lp-Norm Multiple Kernel Learning Marius Kloft, Ulf Brefeld, Sören Sonnenburg, Alexander Zien

NeurIPS 2011 The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning Marius Kloft, Gilles Blanchard

ECML-PKDD 2011 Transfer Learning with Adaptive Regularizers Ulrich Rückert, Marius Kloft

ECML-PKDD 2010 A Unifying View of Multiple Kernel Learning Marius Kloft, Ulrich Rückert, Peter L. Bartlett

AISTATS 2010 Online Anomaly Detection Under Adversarial Impact Marius Kloft, Pavel Laskov

ECML-PKDD 2009 Active and Semi-Supervised Data Domain Description Nico Görnitz, Marius Kloft, Ulf Brefeld

NeurIPS 2009 Efficient and Accurate Lp-Norm Multiple Kernel Learning Marius Kloft, Ulf Brefeld, Pavel Laskov, Klaus-Robert Müller, Alexander Zien, Sören Sonnenburg

ECML-PKDD 2009 Feature Selection for Density Level-Sets Marius Kloft, Shinichi Nakajima, Ulf Brefeld