Publications
Preprints
C. Chatzis, C. Schenker, M. Pfeffer, E. Acar:
tPARAFAC2: Tracking evolving patterns in (incomplete) temporal data. (2024)
[bibtex],[arxiv]J. König, M. Pfeffer, M. Stoll:
Efficient training of Gaussian processes with tensor product structure. (2023)
[bibtex],[arxiv]K. Kour, S. Dolgov, P. Benner, M. Stoll, M. Pfeffer:
A weighted subspace exponential kernel for support tensor machines. (2023)
[bibtex],[arxiv]
Journal Articles
F. Reggiani, Z. El Rashed, M. Petito, M. Pfeffer, A. Morabito, E. T. Tanda, F. Spagnolo, M. Croce, U. Pfeffer, A. Amaro:
Machine Learning Methods for Gene Selection in Uveal Melanoma.
International Journal of Molecular Sciences 25(3) (2024)
[bibtex],[link]M. Pfeffer, J. Samper:
The cone of 5×5 completely positive matrices.
Discrete & Computational Geometry (2024)
[bibtex],[link],[arxiv]A. Amaro, M. Pfeffer, U. Pfeffer, F. Reggiani:
Evaluation and Comparison of Multi-Omics Data Integration Methods for Subtyping of Cutaneous Melanoma.
Biomedicines 10(12) (2022)
[bibtex],[link]H. Eisenmann, F. Krahmer, M. Pfeffer, A. Uschmajew:
Riemannian thresholding methods for row-sparse and low-rank matrix recovery.
Numerical Algorithms (2022)
[bibtex],[link],[arxiv]M. Bachmayr, M. Götte, M. Pfeffer:
Particle number conservation and block structures in Matrix Product States.
Calcolo 59, 24 (2022)
[bibtex],[link],[arxiv]C. Krumnow, M. Pfeffer, A. Uschmajew:
Computing eigenspaces with low rank constraints.
SIAM Journal on Scientific Computing, 43 (2021) 1, p. 586-608
[bibtex],[link],[preprint]M. Eigel, M. Marschall, M. Pfeffer, R. Schneider:
Adaptive Stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations.
Numerische Mathematik, 145 (2020) 3, p. 655-692
[bibtex],[link],[arxiv]M. Pfeffer, A. Seigal, B. Sturmfels:
Learning paths from signature tensors.
SIAM journal on matrix analysis and applications, 40 (2019) 2, p. 394-416
[bibtex],[link],[arxiv],[github]M. Pfeffer, A. Uschmajew, A. Amaro, U. Pfeffer:
Data fusion techniques for the integration of multi-domain genomic data from uveal melanoma.
Cancers, 11 (2019) 10, 1434
[bibtex],[link],[preprint]M. Eigel, M. Pfeffer, R. Schneider:
Adaptive stochastic Galerkin FEM with hierarchical tensor representations.
Numerische Mathematik, 136 (2017) 3, p. 765-803
[bibtex],[link],[preprint]S. Szalay, M. Pfeffer, V. Murg, G. Barcza, F. Verstraete, R. Schneider, Ö. Legeza:
Tensor product methods and entanglement optimization for ab initio quantum chemistry.
International journal of quantum chemistry, 115 (2015) 19, p. 1342-1391
[bibtex],[link],[arxiv]
Theses
M. Pfeffer: Tensor methods for the numerical solution of high-dimensional parametric partial differential equations.
Dissertation, Technische Universität Berlin, 2018
[bibtex],[link]M. Pfeffer: Aspects of second-order optimization on fixed rank tensor manifolds.
Masterarbeit, Technische Universität Berlin, 2015M. Pfeffer: Dynamical low rank approximation in novel TT format.
Bachelorarbeit, Technische Universität Berlin, 2011