Accelerating Generalized Linear Models by Trading off Computation for Uncertainty. - Lukas Tatzel; Jonathan Wenger; Frank Schneider 001; Philipp Hennig (CoRR, 2023)

ViViT: Curvature Access Through The Generalized Gauss-Newton's Low-Rank Structure. - Felix Dangel; Lukas Tatzel; Philipp Hennig (Trans. Mach. Learn. Res., 2023)

Reparameterization invariance in approximate Bayesian inference. - Hrittik Roy; Marco Miani; Carl Henrik Ek; Philipp Hennig; Marvin Pförtner; Lukas Tatzel; Søren Hauberg (NeurIPS, 2024)

Debiasing Mini-Batch Quadratics for Applications in Deep Learning. - Lukas Tatzel; Bálint Mucsányi; Osane Hackel; Philipp Hennig (ICLR, 2025)

Accelerating Non-Conjugate Gaussian Processes By Trading Off Computation For Uncertainty. - Lukas Tatzel; Jonathan Wenger; Frank Schneider 001; Philipp Hennig (Trans. Mach. Learn. Res., 2025)

Position: Curvature Matrices Should Be Democratized via Linear Operators. - Felix Dangel; Runa Eschenhagen; Weronika Ormaniec; Andres Fernandez; Lukas Tatzel; Agustinus Kristiadi (CoRR, 2025)