Chen Qiu

According to our database, Chen Qiu authored at least 17 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Self-Supervised Anomaly Detection With Neural Transformations.

Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

IEEE Trans. Pattern Anal. Mach. Intell., March, 2025

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

Lorenzo Perini, Maja Rudolph, Sabrina Schmedding, Chen Qiu

Trans. Mach. Learn. Res., 2025

2024

Anomaly Detection of Tabular Data Using LLMs.

Aodong Li, Yunhan Zhao, Chen Qiu, Marius Kloft, Padhraic Smyth, Maja Rudolph, Stephan Mandt

CoRR, 2024

2023

Self-Supervised Anomaly Detection with Neural Transformations.

Chen Qiu

PhD thesis, 2023

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

Clement Fung, Chen Qiu, Aodong Li, Maja Rudolph

CoRR, 2023

Zero-Shot Anomaly Detection without Foundation Models.

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

CoRR, 2023

Zero-Shot Anomaly Detection via Batch Normalization.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Anomaly Detection under Labeling Budget Constraints.

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

Proceedings of the International Conference on Machine Learning, 2023

2022

Detecting Anomalies within Time Series using Local Neural Transformations.

Tim Schneider, Chen Qiu, Marius Kloft, Decky Aspandi-Latif, Steffen Staab, Stephan Mandt, Maja Rudolph

CoRR, 2022

Raising the Bar in Graph-level Anomaly Detection.

Chen Qiu, Marius Kloft, Stephan Mandt, Maja Rudolph

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Latent Outlier Exposure for Anomaly Detection with Contaminated Data.

Chen Qiu, Aodong Li, Marius Kloft, Maja Rudolph, Stephan Mandt

Proceedings of the International Conference on Machine Learning, 2022

2021

History Marginalization Improves Forecasting in Variational Recurrent Neural Networks.

Chen Qiu, Stephan Mandt, Maja Rudolph

Entropy, 2021

Switching Recurrent Kalman Networks.

Giao Nguyen-Quynh, Philipp Becker, Chen Qiu, Maja Rudolph, Gerhard Neumann

CoRR, 2021

Neural Transformation Learning for Deep Anomaly Detection Beyond Images.

Chen Qiu, Timo Pfrommer, Marius Kloft, Stephan Mandt, Maja Rudolph

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Variational Dynamic Mixtures.

Chen Qiu, Stephan Mandt, Maja Rudolph

CoRR, 2020

Deterministic Inference of Neural Stochastic Differential Equations.

Andreas Look, Chen Qiu, Maja Rudolph, Jan Peters, Melih Kandemir

CoRR, 2020

2019

Learning Topometric Semantic Maps from Occupancy Grids.

Markus Hiller, Chen Qiu, Florian Particke, Christian Hofmann, Jörn Thielecke

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019