Seguir
Chen Qiu
Chen Qiu
Research Scientist, Bosch Center for AI
Dirección de correo verificada de us.bosch.com
Título
Citado por
Citado por
Año
Neural transformation learning for deep anomaly detection beyond images
C Qiu, T Pfrommer, M Kloft, S Mandt, M Rudolph
International conference on machine learning, 8703-8714, 2021
1562021
Latent Outlier Exposure for Anomaly Detection with Contaminated Data
C Qiu, A Li, M Kloft, M Rudolph, S Mandt
International Conference on Machine Learning, 18153-18167, 2022
652022
Raising the Bar in Graph-level Anomaly Detection
C Qiu, M Kloft, S Mandt, M Rudolph
International Joint Conference on Artificial Intelligence, 2022
592022
Learning topometric semantic maps from occupancy grids
M Hiller, C Qiu, F Particke, C Hofmann, J Thielecke
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
332019
Zero-shot anomaly detection via batch normalization
A Li, C Qiu, M Kloft, P Smyth, M Rudolph, S Mandt
Advances in Neural Information Processing Systems 36, 40963-40993, 2023
252023
Detecting anomalies within time series using local neural transformations
T Schneider, C Qiu, M Kloft, DA Latif, S Staab, S Mandt, M Rudolph
arXiv preprint arXiv:2202.03944, 2022
242022
Deep anomaly detection under labeling budget constraints
A Li, C Qiu, M Kloft, P Smyth, S Mandt, M Rudolph
International Conference on Machine Learning, 19882-19910, 2023
162023
Federated text-driven prompt generation for vision-language models
C Qiu, X Li, CK Mummadi, MR Ganesh, Z Li, L Peng, WY Lin
The Twelfth International Conference on Learning Representations, 2024
12*2024
Anomaly detection of tabular data using llms
A Li, Y Zhao, C Qiu, M Kloft, P Smyth, M Rudolph, S Mandt
arXiv preprint arXiv:2406.16308, 2024
52024
Switching recurrent Kalman networks
G Nguyen-Quynh, P Becker, C Qiu, M Rudolph, G Neumann
arXiv preprint arXiv:2111.08291, 2021
52021
Self-Supervised Anomaly Detection with Neural Transformations
C Qiu, M Kloft, S Mandt, M Rudolph
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
22024
Model Selection of Anomaly Detectors in the Absence of Labeled Validation Data
C Fung, C Qiu, A Li, M Rudolph
arXiv preprint arXiv:2310.10461, 2023
22023
Switching recurrent kalman network
G Nguyen, C Qiu, P Becker, M Rudolph, G Neumann
US Patent App. 17/516,330, 2023
22023
Anomalous region detection with local neural transformations
M Rudolph, C Qiu, T Schneider
US Patent App. 17/372,204, 2023
22023
Machine learned anomaly detection
C Qiu, MR Rudolph, T Pfrommer
US Patent App. 17/651,917, 2022
22022
Forecasting with deep state space models
C Qiu, MR Rudolph
US Patent App. 17/407,621, 2022
22022
History marginalization improves forecasting in variational recurrent neural networks
C Qiu, S Mandt, M Rudolph
Entropy 23 (12), 1563, 2021
2*2021
Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
L Perini, M Rudolph, S Schmedding, C Qiu
arXiv preprint arXiv:2405.13699, 2024
12024
Predicting a state of a computer-controlled entity
A Look, C Qiu, M Kandemir
US Patent App. 17/231,757, 2021
12021
Adaptively centered representation for zero-shot anomaly detection methods
C Qiu, M Rudolph, A Li
US Patent App. 18/170,253, 2024
2024
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20