5 citations · 18 across the 18 of their papers we have counts for
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A parallel Basis Update and Galerkin Integrator for Tree Tensor Networks
Gianluca Ceruti, Jonas Kusch, Christian Lubich +1
Computing the numerical solution to high-dimensional tensor differential equations can lead to prohibitive computational costs and memory requirements. To reduce the memory and com…
GeoLoRA: Geometric integration for parameter efficient fine-tuning
Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti +2
Low-Rank Adaptation (LoRA) has become a widely used method for parameter-efficient fine-tuning of large-scale, pre-trained neural networks. However, LoRA and its extensions face se…
Randomized low-rank Runge-Kutta methods
Hei Yin Lam, Gianluca Ceruti, Daniel Kressner
This work proposes and analyzes a new class of numerical integrators for computing low-rank approximations to solutions of matrix differential equation. We combine an explicit Rung…
Low-rank Tree Tensor Network Operators for Long-Range Pairwise Interactions
Gianluca Ceruti, Daniel Kressner, Dominik Sulz
Compactly representing and efficently applying linear operators are fundamental ingredients in tensor network methods for simulating quantum many-body problems and solving high-dim…
A robust second-order low-rank BUG integrator based on the midpoint rule
Gianluca Ceruti, Lukas Einkemmer, Jonas Kusch +1
Dynamical low-rank approximation has become a valuable tool to perform an on-the-fly model order reduction for prohibitively large matrix differential equations. A core ingredient…