Maja Rudolph - RankMe

48 papers A* 8Journal 36Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Formally Exploring Time-Series Anomaly Detection Evaluation Metrics. CoRR Dennis Wagner, Arjun Nair, Billy Joe Franks, Justus Arweiler, Aparna Muraleedharan, Indra Jungjohann, Fabian Hartung, Mayank C. Ahuja, Andriy Balinskyy, Saurabh Varshneya, Nabeel Hussain Syed, Mayank Nagda, Philipp Liznerski, Steffen Reithermann, Maja Rudolph, Sebastian J. Vollmer, Ralf Schulz, Torsten Katz, Stephan Mandt, Michael Bortz, Heike Leitte, Daniel Neider, Jakob Burger, Fabian Jirasek, Hans Hasse, Sophie Fellenz, Marius Kloft
2025	J	`jnl`	Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data. IEEE Trans. Artif. Intell. Clement Fung, Chen Qiu, Aodong Li, Maja Rudolph
2025	J	`jnl`	On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. 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 T. 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
2025	J	`jnl`	Self-Supervised Anomaly Detection With Neural Transformations. IEEE Trans. Pattern Anal. Mach. Intell. Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2025	J	`jnl`	Test-time Scaling Techniques in Theoretical Physics - A Comparison of Methods on the TPBench Dataset. CoRR Zhiqi Gao, Tianyi Li, Yurii Kvasiuk, Sai Chaitanya Tadepalli, Maja Rudolph, Daniel J. H. Chung, Frederic Sala, Moritz Münchmeyer
2025	J	`jnl`	Theoretical Physics Benchmark (TPBench) - a Dataset and Study of AI Reasoning Capabilities in Theoretical Physics. CoRR Daniel J. H. Chung, Zhiqi Gao, Yurii Kvasiuk, Tianyi Li, Moritz Münchmeyer, Maja Rudolph, Frederic Sala, Sai Chaitanya Tadepalli
2025	J	`jnl`	Theoretical physics benchmark (TPBench) - a dataset and study of AI reasoning capabilities in theoretical physics. Mach. Learn. Sci. Technol. Daniel J. H. Chung, Zhiqi Gao, Yurii Kvasiuk, Tianyi Li, Moritz Münchmeyer, Maja Rudolph, Frederic Sala, Sai Chaitanya Tadepalli
2025	J	`jnl`	Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior. Trans. Mach. Learn. Res. Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
2024	J	`jnl`	Anomaly Detection of Tabular Data Using LLMs. CoRR Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2024	A*	`conf`	Efficient Integrators for Diffusion Generative Models. ICLR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2024	J	`jnl`	Hybrid Modeling Design Patterns. CoRR Maja Rudolph, Stefan Kurz, Barbara Rakitsch
2024	J	`jnl`	On the Challenges and Opportunities in Generative AI. CoRR 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 T. 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
2024	J	`jnl`	Towards Fast Stochastic Sampling in Diffusion Generative Models. CoRR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2024	J	`jnl`	Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior. CoRR Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu
2023	J	`jnl`	Deep Anomaly Detection on Tennessee Eastman Process Data. CoRR 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 Klöpper, Stephan Mandt, Michael Bortz, Jakob Burger, Hans Hasse, Marius Kloft
2023	A*	`conf`	Deep Anomaly Detection under Labeling Budget Constraints. ICML Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Deep Anomaly Detection under Labeling Budget Constraints. CoRR Aodong Li, Chen Qiu, Padhraic Smyth, Marius Kloft, Stephan Mandt, Maja Rudolph
2023	J	`jnl`	Efficient Integrators for Diffusion Generative Models. CoRR Kushagra Pandey, Maja Rudolph, Stephan Mandt
2023	J	`jnl`	LoRA ensembles for large language model fine-tuning. CoRR Xi Wang, Laurence Aitchison, Maja Rudolph
2023	J	`jnl`	Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data. CoRR Clement Fung, Chen Qiu, Aodong Li, Maja Rudolph
2023	J	`jnl`	TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection. Trans. Mach. Learn. Res. Dennis Wagner, Tobias Michels, Florian C. F. Schulz, Arjun Nair, Maja Rudolph, Marius Kloft
2023	A*	`conf`	Zero-Shot Anomaly Detection via Batch Normalization. NeurIPS Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2023	J	`jnl`	Zero-Shot Anomaly Detection without Foundation Models. CoRR Aodong Li, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Complex-Valued Autoencoders for Object Discovery. CoRR Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
2022	J	`jnl`	Complex-Valued Autoencoders for Object Discovery. Trans. Mach. Learn. Res. Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling
2022	J	`jnl`	Detecting Anomalies within Time Series using Local Neural Transformations. CoRR Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi-Latif, Steffen Staab, Stephan Mandt, Maja Rudolph
2022	A*	`conf`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. ICML Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	J	`jnl`	Latent Outlier Exposure for Anomaly Detection with Contaminated Data. CoRR Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt
2022	A*	`conf`	Modeling Irregular Time Series with Continuous Recurrent Units. ICML Mona Schirmer, Mazin Eltayeb, Stefan Lessmann, Maja Rudolph
2022	A*	`conf`	Raising the Bar in Graph-level Anomaly Detection. IJCAI Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2022	J	`jnl`	Raising the Bar in Graph-level Anomaly Detection. CoRR Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	—	`conf`	Continuous-Discrete Recurrent Kalman Networks for Irregular Time Series. PKDD/ECML Workshops (1) Mona Schirmer, Mazin Eltayeb, Maja Rudolph
2021	J	`jnl`	History Marginalization Improves Forecasting in Variational Recurrent Neural Networks. Entropy Chen Qiu, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Modeling Irregular Time Series with Continuous Recurrent Units. CoRR Mona Schirmer, Mazin Eltayeb, Stefan Lessmann, Maja Rudolph
2021	A*	`conf`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. ICML Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Neural Transformation Learning for Deep Anomaly Detection Beyond Images. CoRR Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph
2021	J	`jnl`	Switching Recurrent Kalman Networks. CoRR Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann
2020	J	`jnl`	Deterministic Inference of Neural Stochastic Differential Equations. CoRR Andreas Look, Chen Qiu, Maja Rudolph, Jan Peters, Melih Kandemir
2020	J	`jnl`	Variational Dynamic Mixtures. CoRR Chen Qiu, Stephan Mandt, Maja Rudolph
2019	J	`jnl`	Extending Machine Language Models toward Human-Level Language Understanding. CoRR James L. McClelland, Felix Hill, Maja Rudolph, Jason Baldridge, Hinrich Schütze
2018	A*	`conf`	Dynamic Embeddings for Language Evolution. WWW Maja Rudolph, David M. Blei
2018	—	`—`	Exponential Family Embeddings. Maja Rudolph
2017	J	`jnl`	Dynamic Bernoulli Embeddings for Language Evolution. CoRR Maja Rudolph, David M. Blei
2017	—	`conf`	Structured Embedding Models for Grouped Data. NIPS Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei
2017	J	`jnl`	Structured Embedding Models for Grouped Data. CoRR Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei
2016	J	`jnl`	Edward: A library for probabilistic modeling, inference, and criticism. CoRR Dustin Tran, Alp Kucukelbir, Adji B. Dieng, Maja Rudolph, Dawen Liang, David M. Blei
2016	—	`conf`	Exponential Family Embeddings. NIPS Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei
2016	J	`jnl`	Exponential Family Embeddings. CoRR Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei