Sweep Algorithms for the Capacitated Vehicle Routing Problem with Structured Time Windows. - Christoph Hertrich; Philipp Hungerländer; Christian Truden (OR, 2018)

Decision Support for Material Procurement. - Heiner Ackermann; Erik Diessel; Michael Helmling; Christoph Hertrich; Neil Jami; Johanna Schneider (OR, 2019)

Scheduling a Proportionate Flow Shop of Batching Machines. - Christoph Hertrich (OR, 2019)

Sweep Algorithms for the Capacitated Vehicle Routing Problem with Structured Time Window. - Christoph Hertrich; Philipp Hungerländer; Christian Truden (CoRR, 2019)

Scheduling a proportionate flow shop of batching machines. - Christoph Hertrich; Christian Weiß 003; Heiner Ackermann; Sandy Heydrich; Sven O. Krumke (J. Sched., 2020)

ReLU Neural Networks for Exact Maximum Flow Computation. - Christoph Hertrich; Leon Sering (CoRR, 2021)

Coloring Drawings of Graphs. - Christoph Hertrich; Felix Schröder; Raphael Steiner (Electron. J. Comb., 2022)

The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality. - Vincent Froese; Christoph Hertrich; Rolf Niedermeier (J. Artif. Intell. Res., 2022)

Online algorithms to schedule a proportionate flexible flow shop of batching machines. - Christoph Hertrich; Christian Weiß 003; Heiner Ackermann; Sandy Heydrich; Sven O. Krumke (J. Sched., 2022)

Facets of neural network complexity. - Christoph Hertrich (2022)

Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes. - Christian Haase 001; Christoph Hertrich; Georg Loho (ICLR, 2023)

Training Fully Connected Neural Networks is ∃R-Complete. - Daniel Bertschinger; Christoph Hertrich; Paul Jungeblut; Tillmann Miltzow; Simon Weber 001 (NeurIPS, 2023)

Training Neural Networks is NP-Hard in Fixed Dimension. - Vincent Froese; Christoph Hertrich (NeurIPS, 2023)

Mode Connectivity in Auction Design. - Christoph Hertrich; Yixin Tao; László A. Végh (NeurIPS, 2023)

Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size. - Christoph Hertrich; Martin Skutella (INFORMS J. Comput., 2023)

Towards Lower Bounds on the Depth of ReLU Neural Networks. - Christoph Hertrich; Amitabh Basu; Marco Di Summa; Martin Skutella (SIAM J. Discret. Math., 2023)

A First Order Method for Linear Programming Parameterized by Circuit Imbalance. - Richard Cole 001; Christoph Hertrich; Yixin Tao; László A. Végh (IPCO, 2024)

Neural Networks and (Virtual) Extended Formulations. - Christoph Hertrich; Georg Loho (CoRR, 2024)

Open Problem: Fixed-Parameter Tractability of Zonotope Problems. - Vincent Froese; Moritz Grillo; Christoph Hertrich; Martin Skutella (COLT, 2025)

Decomposition Polyhedra of Piecewise Linear Functions. - Marie-Charlotte Brandenburg; Moritz Leo Grillo; Christoph Hertrich (ICLR, 2025)

Depth-Bounds for Neural Networks via the Braid Arrangement. - Moritz Grillo; Christoph Hertrich; Georg Loho (CoRR, 2025)

ReLU neural networks of polynomial size for exact maximum flow computation. - Christoph Hertrich; Leon Sering (Math. Program., 2025)

On the Depth of Monotone ReLU Neural Networks and ICNNs. - Egor Bakaev; Florestan Brunck; Christoph Hertrich; Daniel Reichman 001; Amir Yehudayoff (CoRR, 2025)

Better Neural Network Expressivity: Subdividing the Simplex. - Egor Bakaev; Florestan Brunck; Christoph Hertrich; Jack Stade; Amir Yehudayoff (CoRR, 2025)

The Computational Complexity of Counting Linear Regions in ReLU Neural Networks. - Moritz Stargalla; Christoph Hertrich; Daniel Reichman 001 (CoRR, 2025)