Adaptive stochastic Galerkin FEM with hierarchical tensor representations. - Martin Eigel; Max Pfeffer; Reinhold Schneider (Numerische Mathematik, 2017)

Learning Paths from Signature Tensors. - Max Pfeffer; Anna Seigal; Bernd Sturmfels (SIAM J. Matrix Anal. Appl., 2019)

Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations. - Martin Eigel; Manuel Marschall; Max Pfeffer; Reinhold Schneider (Numerische Mathematik, 2020)

Particle Number Conservation and Block Structures in Matrix Product States. - Markus Bachmayr; Michael Götte; Max Pfeffer (CoRR, 2021)

Computing Eigenspaces With Low Rank Constraints. - Christian Krumnow; Max Pfeffer; André Uschmajew (SIAM J. Sci. Comput., 2021)

A Time-Aware Tensor Decomposition for Tracking Evolving Patterns. - Christos Chatzis; Max Pfeffer; Pedro G. Lind; Evrim Acar (MLSP, 2023)

A weighted subspace exponential kernel for support tensor machines. - Kirandeep Kour; Sergey Dolgov; Peter Benner; Martin Stoll; Max Pfeffer (CoRR, 2023)

Riemannian thresholding methods for row-sparse and low-rank matrix recovery. - Henrik Eisenmann; Felix Krahmer; Max Pfeffer; André Uschmajew (Numer. Algorithms, 2023)

tPARAFAC2: Tracking evolving patterns in (incomplete) temporal data. - Christos Chatzis; Carla Schenker; Max Pfeffer; Evrim Acar (CoRR, 2024)

The Cone of 5˟ 5 Completely Positive Matrices. - Max Pfeffer; José Alejandro Samper (Discret. Comput. Geom., 2024)

The Intrinsic Riemannian Proximal Gradient Method for Nonconvex Optimization. - Ronny Bergmann; Hajg Jasa; Paula John; Max Pfeffer (CoRR, 2025)

The Intrinsic Riemannian Proximal Gradient Method for Convex Optimization. - Ronny Bergmann; Hajg Jasa; Paula John; Max Pfeffer (CoRR, 2025)