Interacting with fallible AI: Is distrust helpful when receiving AI misclassifications?
T.M. Peters, I. Scharlau, Frontiers in Psychology 16 (n.d.).

MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations
A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.

Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning
M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.

Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor
A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.

Robust vehicle localization based on multi-level sensor fusion and online parameter estimation
M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–242.

Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning
M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.

Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition
S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 17 (2009) 1577–1590.