Nonlinear Image Processing and Filtering: A Unified Approach Based on Vertically Weighted Regression. - Ewaryst Rafajlowicz; Miroslaw Pawlak; Ansgar Steland (Int. J. Appl. Math. Comput. Sci., 2008)

Nonparametric sequential change-point detection by a vertically trimmed box method. - Ewaryst Rafajlowicz; Miroslaw Pawlak; Ansgar Steland (IEEE Trans. Inf. Theory, 2010)

New approaches to nonparametric density estimation and selection of smoothing parameters. - Nina Golyandina; Andrey Pepelyshev; Ansgar Steland (Comput. Stat. Data Anal., 2012)

Sequential Data-Adaptive Bandwidth Selection by Cross-Validation for Nonparametric Prediction. - Ansgar Steland (Commun. Stat. Simul. Comput., 2012)

Nonparametric Sequential Signal Change Detection Under Dependent Noise. - Miroslaw Pawlak; Ansgar Steland (IEEE Trans. Inf. Theory, 2013)

On Convergence of Moments for Approximating Processes and Applications to Surrogate Models. - Ansgar Steland (CoRR, 2018)

Automatic processing and solar cell detection in photovoltaic electroluminescence images. - Evgenii Sovetkin; Ansgar Steland (Integr. Comput. Aided Eng., 2019)

Extreme Learning and Regression for Objects Moving in Non-Stationary Spatial Environments. - Ansgar Steland (CoRR, 2020)

Testing and estimating change-points in the covariance matrix of a high-dimensional time series. - Ansgar Steland (J. Multivar. Anal., 2020)

Cross-Validation and Uncertainty Determination for Randomized Neural Networks with Applications to Mobile Sensors. - Ansgar Steland; Bart E. Pieters (CoRR, 2021)

Segmentation of photovoltaic module cells in uncalibrated electroluminescence images. - Sergiu Deitsch; Claudia Buerhop-Lutz; Evgenii Sovetkin; Ansgar Steland; Andreas Maier 001; Florian Gallwitz; Christian Riess (Mach. Vis. Appl., 2021)

Is there a role for statistics in artificial intelligence? - Sarah Friedrich; Gerd Antes; Sigrid Behr; Harald Binder; Werner Brannath; Florian Dumpert; Katja Ickstadt; Hans A. Kestler; Johannes Lederer; Heinz Leitgöb; Markus Pauly; Ansgar Steland; et al. (Adv. Data Anal. Classif., 2022)

On Extreme Value Asymptotics of Projected Sample Covariances in High Dimensions with Applications in Finance and Convolutional Networks. - Ansgar Steland (CoRR, 2023)

Efficiently Computable Safety Bounds for Gaussian Processes in Active Learning. - Jörn Tebbe; Christoph Zimmer; Ansgar Steland; Markus Lange-Hegermann; Fabian Mies (AISTATS, 2024)

Flexible nonlinear inference and change-point testing of high-dimensional spectral density matrices. - Ansgar Steland (J. Multivar. Anal., 2024)