Computing the Chow Variety of Quadratic Space Curves. - Peter Bürgisser; Kathlén Kohn; Pierre Lairez; Bernd Sturmfels (MACIS, 2015)

Changing Views on Curves and Surfaces. - Kathlén Kohn; Bernd Sturmfels; Matthew Trager (CoRR, 2017)

Voronoi Cells of Lattices with Respect to Arbitrary Norms. - Johannes Blömer; Kathlén Kohn (SIAM J. Appl. Algebra Geom., 2018)

Pure and Spurious Critical Points: a Geometric Study of Linear Networks. - Matthew Trager; Kathlén Kohn; Joan Bruna (ICLR, 2020)

Projective Geometry of Wachspress Coordinates. - Kathlén Kohn; Kristian Ranestad (Found. Comput. Math., 2020)

Coisotropic hypersurfaces in Grassmannians. - Kathlén Kohn (J. Symb. Comput., 2021)

Invariant Theory and Scaling Algorithms for Maximum Likelihood Estimation. - Carlos Améndola; Kathlén Kohn; Philipp Reichenbach; Anna Seigal (SIAM J. Appl. Algebra Geom., 2021)

Snapshot of Algebraic Vision. - Joe Kileel 001; Kathlén Kohn (CoRR, 2022)

Geometry of Linear Convolutional Networks. - Kathlén Kohn; Thomas Merkh; Guido Montúfar; Matthew Trager (SIAM J. Appl. Algebra Geom., 2022)

Voronoi diagrams of algebraic varieties under polyhedral norms. - Adrian Becedas; Kathlén Kohn; Lorenzo Venturello (J. Symb. Comput., 2024)

Differential Equations for Gaussian Statistical Models with Rational Maximum Likelihood Estimator. - Carlos Améndola; Lukas Gustafsson; Kathlén Kohn; Orlando Marigliano; Anna Seigal (SIAM J. Appl. Algebra Geom., 2024)

Corrigendum: Invariant Theory and Scaling Algorithms for Maximum Likelihood Estimation. - Carlos Améndola; Kathlén Kohn; Philipp Reichenbach; Anna Seigal (SIAM J. Appl. Algebra Geom., 2024)

Function Space and Critical Points of Linear Convolutional Networks. - Kathlén Kohn; Guido Montúfar; Vahid Shahverdi; Matthew Trager (SIAM J. Appl. Algebra Geom., 2024)

A Bridge between Invariant Theory and Maximum Likelihood Estimation. - Carlos Améndola; Kathlén Kohn; Philipp Reichenbach; Anna Seigal (SIAM Rev., 2024)

PLMP - Point-Line Minimal Problems in Complete Multi-View Visibility. - Timothy Duff; Kathlén Kohn; Anton Leykin; Tomás Pajdla (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

PL1P: Point-Line Minimal Problems under Partial Visibility in Three Views. - Timothy Duff; Kathlén Kohn; Anton Leykin; Tomás Pajdla (Int. J. Comput. Vis., 2024)

On the Geometry and Optimization of Polynomial Convolutional Networks. - Vahid Shahverdi; Giovanni Luca Marchetti; Kathlén Kohn (AISTATS, 2025)

Order-One Rolling Shutter Cameras. - Marvin Anas Hahn; Kathlén Kohn; Orlando Marigliano; Tomás Pajdla (CVPR, 2025)

Geometry of Lightning Self-Attention: Identifiability and Dimension. - Nathan W. Henry; Giovanni Luca Marchetti; Kathlén Kohn (ICLR, 2025)

Geometry of Linear Neural Networks: Equivariance and Invariance Under Permutation Groups. - Kathlén Kohn; Anna-Laura Sattelberger; Vahid Shahverdi (SIAM J. Matrix Anal. Appl., 2025)

An Invitation to Neuroalgebraic Geometry. - Giovanni Luca Marchetti; Vahid Shahverdi; Stefano Mereta; Matthew Trager; Kathlén Kohn (CoRR, 2025)

PLMP - Point-Line Minimal Problems for Projective SfM. - Kim Kiehn; Albin Ahlbäck; Kathlén Kohn (CoRR, 2025)

A Framework for Reducing the Complexity of Geometric Vision Problems and its Application to Two-View Triangulation with Approximation Bounds. - Felix Rydell; Georg Bökman; Fredrik Kahl; Kathlén Kohn (CoRR, 2025)

An Algebraic Geometry Approach to Viewing Graph Solvability. - Federica Arrigoni; Kathlén Kohn; Andrea Fusiello; Tomás Pajdla (CoRR, 2025)

Learning on a Razor's Edge: the Singularity Bias of Polynomial Neural Networks. - Vahid Shahverdi; Giovanni Luca Marchetti; Kathlén Kohn (CoRR, 2025)

The Riemannian Geometry associated to Gradient Flows of Linear Convolutional Networks. - El Mehdi Achour; Kathlén Kohn; Holger Rauhut (CoRR, 2025)