TRR 391 Working Papers

Mahtout, B. E., Ziel, F. (2026). Electricity Price Forecasting: Bridging Linear Models, Neural Networks and Online Learning. arXiv. DOI: 10.48550/arXiv.2601.02856.

Kucharský, Š., Mishra, A., Habermann, D., Radev, S. T., Bürkner, P. C. (2026). Improving the Accuracy of Amortized Model Comparison with Self-Consistency. arXiv. DOI: 10.48550/arXiv.2512.14308.

Jedhoff, S., Semenova, E., Raulo, A., Meyer, A., Bürkner, P. C. (2026). From Mice to Trains: Amortized Bayesian Inference on Graph Data. arXiv. DOI: 10.48550/arXiv.2601.02241.

Ng, W. L., Tang, X., Cheung, M. L., Gao, J., Yau, C. Y., Dette, H. (2026). Inference for Multiple Change-points in Piecewise Locally Stationary Time Series. arXiv. DOI: 10.48550/arXiv.2601.07400.

Mukherjee, S., Aguilar, J. E., Zago, M., Claassen, M., Bürkner, P. C. (2025). Latent variable estimation with composite Hilbert space Gaussian processes. arXiv. DOI: 10.48550/arXiv.2510.25371.

Bracher, N., Kühmichel, L., Ivanova, D. R., Intes, X., Bürkner, P. C., Radev, S. T. (2025). JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference. arXiv. DOI: 10.48550/arXiv.2512.22999.

Fazio, L., Scholz, M., Aguilar, J. E., Bürkner, P. C. (2025). Primed Priors for Simulation-Based Validation of Bayesian Models. arXiv. DOI: 10.48550/arXiv.2408.06504.

Lederer, J., Oesting, M. (2025). Extremes in High Dimensions: Methods and Scalable Algorithms. arXiv. DOI: 10.48550/arXiv.2303.04258.

Kutta, T., Schumann, M., Dette, H. (2025). Inference for Forecasting Accuracy: Pooled versus Individual Estimators in High-dimensional Panel Data. arXiv. DOI: 10.48550/arXiv.2512.15592.

Li, B., Qiao, X., Wu, W., Dette, H. (2025). Convergence of covariance and spectral density estimates for high-dimensional functional time series. arXiv. DOI: 10.48550/arXiv.2512.13310.

Helmer, V. (2025). Modal Split Perceptions and Preferences for Public Funding. TRR 391 Working Paper #10. DOI: 10.17877/DE290R-26254.

Boulin, A., Haufs., E. (2025). Extrapolating into the Extremes with Minimum Distance Estimation. arXiv. DOI: 10.48550/arXiv.2511.20466.

Aguilar, J. E., Kohns, D., Vehtari, A., Bürkner, P. C. (2025). R2 priors for Grouped Variance Decomposition in High-dimensional Regression. arXiv. DOI: 10.48550/arXiv.2507.11833.

Bastian, P., Dette, H., Dunsche, M. (2025). Differentially private testing for relevant dependencies in high dimensions. arXiv. DOI: 10.48550/arXiv.2511.17167.

Kutta, T., Dette, H., Wang, S. (2025). Multiscale Change Point Detection for Functional Time Series. arXiv. DOI: 10.48550/arXiv.2511.06870.

Flossdorf, J., Meyer, A., Artjuch, D., Schneider, J., Jentsch, C. (2025). Unsupervised Movement Detection in Indoor Positioning Systems of Production Halls. TRR 391 Working Paper #9. DOI: 10.17877/DE290R-25841.

Demetrescu M., Schmidt, F. , Taylor. A. M. R. (2025). Real-Time Monitoring for Stock Return Predictability in Nonstationary Volatility Environments. TRR 391 Working Paper #8. DOI: 10.17877/DE290R-25840.

Lebedev, A., Das, A., Pappert, S., Schlüter, S. (2025). Analyzing Uncertainty Quantification in Statistical and Deep Learning Models for Probabilistic Electricity Price Forecasting. arXiv. DOI: 10.48550/arXiv.2509.19417.

Pappert, S. (2025). The Field Equations of Penalized non-Parametric Regression. arXiv. DOI: 10.48550/arXiv.2503.14763.

Bai, L., Dette, H. (2025). Measuring deviations from spherical symmetry. arXiv. DOI: 10.48550/arXiv.2510.18598.

Bastian, P., Kutta, T., Basu, R., Dette, H. (2025). Monitoring Time Series for Relevant Changes. arXiv. DOI: 10.48550/arXiv.2509.01756.

Quanz, P., Dette, H. (2025). Practically significant change points in high dimension - measuring signal strength pro active component. arXiv. DOI: 10.48550/arXiv.2508.21520.

Dette, H., Kühnert, S. (2025). Pivotal inference for linear predictions in stationary processes. arXiv. DOI: 10.48550/arXiv.2508.21025.

Hoenow, C., Helmers, V., Yang, E. (2025). Electric Bicycles and Public Transport Tickets: Ownership and Car Use Patterns. TRR 391 Working Paper #7. DOI: 10.17877/DE290R-25610.

Kühnert, S., Park, J. (2025). Functional Periodic ARMA Processes. arXiv. DOI: 10.48550/arXiv.2507.18962.

Boulin, A., Bücher, A. (2025). Structured linear factor models for tail dependence. arXiv. DOI: 10.48550/arXiv.2507.16340.  

Püttschneider, J., Heilig, S., Fischer, A., Faulwasser, T. (2025). Towards an Optimal Control Perspective of ResNet Training. TRR 391 Working Paper #6. DOI: 10.17877/DE290R-25566.

Faymonville, M. , Jentsch, C. (2025). Joint semi-parametric INAR bootstrap inference for model coefficients and innovation distribution. arXiv. DOI: 10.48550/arXiv.2507.11124.

Faymonville, M., Jentsch, C., Paparoditis, E. (2025). Predictive inference for discrete-valued time series. arXiv. DOI: 10.48550/arXiv.2507.16035.

Mohaddes, A., Iafrate, F., Lederer, J. (2025). Regularized Learning for Fractional Brownian Motion via Path Signatures. arXiv. DOI: 10.48550/arXiv.2506.16156.

Dette, H., Möllenhoff, K., Wied, D. (2025). Practically significant differences between conditional distribution functions. arXiv. DOI: 10.48550/arXiv.2506.06545.

Aguilar, J. E., Bürkner P. C. (2025). Dependency-aware shrinkage priors for high dimensional regression. arXiv. DOI: 10.48550/arXiv.2505.10715.

Jedhoff, S., Kutabi H., Meyer A. Bürkner P. C. (2025). Efficient uncertainty propagation in Bayesian two-step procedures. arXiv. DOI: 10.48550/arXiv.2505.10510.

Mukherjee, S., Claassen M., Bürkner P. C. (2025). Hilbert space methods for approximating multi-output latent variable Gaussian processes. arXiv. DOI: 10.48550/arXiv.2505.16919.

Scheurer, S., Reiser P., Brünnette T., Nowak W., Guthke A., Bürkner P. C. (2025). Uncertainty-aware surrogate-based amortized Bayesian inference for computationally expensive models. arXiv. DOI: 10.48550/arXiv.2505.08683.

Lederer, J., Sabourin, A., Taheri, M. (2025). Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees. arXiv. DOI: 10.48550/arXiv.2505.22371.

Taheri, M., Lederer, J. (2025). Regularization can make diffusion models more efficient. arXiv. DOI: 10.48550/arXiv.2502.09151.

Andor, M. A., Hoenow, N. C.,  Hümmecke, E., Tomberg, L. (2025). Small Payments Can Help Take Cars Off the Road Cost-Effectively. TRR 391 Working Paper #5. DOI: 10.17877/DE290R-25478.

Lindenau, R., Demetrescu, M. (2025). (When) Do persistent predictors predict stock returns directionally? TRR 391 Working Paper #4. DOI: 10.17877/DE290R-25452.

Bastian, P., Dette, H. (2025). Multiscale detection of practically significant changes in a gradually varying time series. arXiv. DOI: 10.48550/arXiv.2504.15872.

Bastian, P., Bissantz, N. (2025). Detecting relevant dependencies under measurement error with applications to the analysis of planetary system evolution. arXiv. DOI: 10.48550/arXiv.2504.05055.

Kühnert, S., Rice, G., Aue, A. (2025). Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes. arXiv. DOI: 10.48550/arXiv.2407.12221.

Elsemüller L., Pratz V., von Krause M., Voss A., Bürkner P. C., Radev S. T. (2025). Does unsupervised domain adaptation improve the robustness of amortized Bayesian inference? a systematic evaluation. arXiv. DOI: 10.48550/arXiv.2502.04949.

Mishra A., Habermann D., Schmitt M., Radev S. T., Bürkner P. C. (2025). Robust amortized Bayesian inference with self-consistency losses on unlabeled data. arXiv. DOI: 10.48550/arXiv.2501.13483.

Kucharský Š., Bürkner P. C. (2025). Amortized Bayesian mixture models. arXiv. DOI: 10.48550/arXiv.2501.10229.

Uniejewski, B., Ziel, F. (2025). Probabilistic forecasts of load, solar and wind for electricity price forecasting. arXiv. DOI: 10.48550/arXiv.2501.06180.

Bastian, P., Dette, H., Heinrichs, F. (2025). Sequential outlier detection in non-stationary time series. arXiv. DOI: 10.48550/arXiv.2502.18038.

Bastian, P., Basu, R., Dette, H. (2025). Uniform confidence bands for joint angles across different fatigue phases. arXiv. DOI: 10.48550/arXiv.2502.08430.

Andor, M.A., Flintz, J., Vance, C. (2025). Individual mobility and public transport subsidies. TRR 391 Working Paper #1. DOI: 10.17877/DE290R-25228.

Bastian, P. (2025). Choosing the right norm for change point detection in functional data. arXiv. DOI: 10.48550/arXiv.2501.04476.

Bai, L., Dette, H., Wu, W. (2025). A Portmanteau test for multivariate non-stationary functional time series with an increasing number of lags. arXiv. DOI: 10.48550/arXiv.2501.00118.

Pappert, S. (2024). Moving aggregate modified autoregressive copula-based time series models (MAGMAR-copulas). arXiv. DOI: 10.48550/arXiv.2402.01491.

Reiser P., Bürkner P. C., Guthke A. (2024). Bayesian surrogate training on multiple data sources: a hybrid modeling strategy. arXiv. DOI: 10.48550/arXiv.2412.11875.

Dette, H., Kroll, M. (2024). Detecting practically significant dependencies in infinite dimensional data via distance correlations. arXiv. DOI: 10.48550/arXiv.2411.16177.

Bastian, P. (2024).  Detecting relevant deviations from the white noise assumption for non-stationary time series. arXiv. DOI: 10.48550/arXiv.2411.06909.

Molodchyk, O., Teutsch, J., Faulwasser, T. (2024). Towards safe Bayesian optimization with Wiener kernel regression. arXiv. DOI: 10.48550/arXiv.2411.02253.

Boulin, A. (2024). Estimating max-stable random vectors with discrete spectral measure using model-based clustering arXiv. DOI: 10.48550/arXiv.2402.01609.