Scientific publications

Accepted

2026

• Mukherjee S., Claassen M., & Bürkner P. C. (2026) Hilbert space methods for approximating multi-output latent variable Gaussian processes. Stat Comput 36, 110. Preprint available for free.

2025

• Mukherjee S., Claassen M. & Bürkner PC. (2025) DGP-LVM: Derivative Gaussian process latent variable models. Stat Comput 35, 120. Preprint available for free.

In Review

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

• Bischoff S., Poličar P. G., Mukherjee S., Macke J. H., Claassen M., & Schröder C. (2025). velotest: Statistical assessment of RNA velocity embeddings reveals quality differences for reliable trajectory visualizations. bioRxiv, 2025-10.

• Zago M., Mukherjee S., Schleicher J. T., Bürkner P. C., Tabatabai G., Claassen M. (2026) G-LATO: Inference of Spatial Latent Ordering via Deep Gaussian Processes. bioRxiv, 2026-06.

Preprint

• Mukherjee S. (2021) Bayesian Analysis of Stochastic Volatility Model using Finite Gaussian Mixtures with Unknown Number of Components. arXiv preprint arXiv:2110.12824.

PhD Thesis

• Mukherjee S. (2025) On Latent Variable Estimation Using Derivative Gaussian Processes, Faculty of Science, University of Tübingen.