activity
20222026
collaborators

6 papers

cs.IT2026

Reliable one-bit quantization of bandlimited graph data via single-shot noise shaping

Johannes Maly, Anna Veselovska

Graph data are ubiquitous in natural sciences and machine learning. In this paper, we consider the problem of quantizing graph structured, bandlimited data to few bits per entry wh…

eess.SP2026

Low-Bit Quantization of Bandlimited Graph Signals via Iterative Methods

Felix Krahmer, He Lyu, Rayan Saab +3

We study the quantization of real-valued bandlimited signals on graphs, focusing on low-bit representations. We propose iterative noise-shaping algorithms for quantization, includi…

cs.LG2024

Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent

Santhosh Karnik, Anna Veselovska, Mark Iwen +1

We provide a rigorous analysis of implicit regularization in an overparametrized tensor factorization problem beyond the lazy training regime. For matrix factorization problems, th…

eess.IV2024

The Mathematics of Dots and Pixels: On the Theoretical Foundations of Image Halftoning

Felix Krahmer, Anna Veselovska

The evolution of image halftoning, from its analog roots to contemporary digital methodologies, encapsulates a fascinating journey marked by technological advancements and creative…

cs.LG2022

Non-intrusive surrogate modelling using sparse random features with applications in crashworthiness analysis

Maternus Herold, Anna Veselovska, Jonas Jehle +1

Efficient surrogate modelling is a key requirement for uncertainty quantification in data-driven scenarios. In this work, a novel approach of using Sparse Random Features for surro…

math.NA2022

Enhanced Digital Halftoning via Weighted Sigma-Delta Modulation

Felix Krahmer, Anna Veselovska

In this paper, we study error diffusion techniques for digital halftoning from the perspective of 1-bit Sigma-Delta quantization. We introduce a method to generate Sigma-Delta sche…