- Mineaki Ohishi. Generalized fused Lasso for grouped data in generalized linear models. Statistics and Computing, 34(4):124, August 2024.
- Beatrice Foroni, Luca Merlo, Lea Petrella. Expectile hidden Markov regression models for analyzing cryptocurrency returns. Statistics and Computing, 34(2):66, 2024.
- Daniel Rudolf, Philip Schär. Dimension-independent spectral gap of polar slice sampling. Statistics and Computing, 34(1):20, February 2024.
- Jan Vávra, Arnost Komárek, Bettina Grün, Gertraud Malsiner-Walli. Clusterwise multivariate regression of mixed-type panel data. Statistics and Computing, 34(1):46, February 2024.
- Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti. Comprehensive study of variational Bayes classification for dense deep neural networks. Statistics and Computing, 34(1):17, February 2024.
- Yu-Chien Bo Ning, Ning Ning. Spike and slab Bayesian sparse principal component analysis. Statistics and Computing, 34(3):118, June 2024.
- Hsin-Hsiung Huang, Feng Yu 0016, Xing Fan, Teng Zhang 0002. A framework of regularized low-rank matrix models for regression and classification. Statistics and Computing, 34(1):10, February 2024.
- Daniel Schalk, Bernd Bischl, David Rügamer. Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models. Statistics and Computing, 34(1):31, February 2024.
- Peter A. Whalley, Daniel Paulin, Benedict J. Leimkuhler. Randomized time Riemannian Manifold Hamiltonian Monte Carlo. Statistics and Computing, 34(1):48, February 2024.
- Michaël Allouche, Stéphane Girard, Emmanuel Gobet. Estimation of extreme quantiles from heavy-tailed distributions with neural networks. Statistics and Computing, 34(1):12, February 2024.