activity
20192026
most citedNonlinear spectral clustering with C++ GraphBLAS

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.DC2026

Beyond Lemma Sharing -- Novel Parallelization Strategies for Property Directed Reachability

Verner Vlačić

Property Directed Reachability (PDR) is a commonly used technique for automated hardware model checking, yet efficiently parallelizing it remains a significant challenge. Existing…

cs.DC2026★ 1 cited

Nonlinear spectral clustering with C++ GraphBLAS

Dimosthenis Pasadakis, Olaf Schenk, Verner Vlacic +1

Nonlinear reformulations of the spectral clustering method have gained a lot of recent attention due to their increased numerical benefits and their solid mathematical background.…

cs.AR2023

ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems

Georgios Zacharopoulos, Ilias Bournias, Verner Vlacic +1

When utilized effectively, Supercloud heterogeneous systems have the potential to significantly enhance performance. Our ReDSEa tool-chain automates the mapping, load balancing, sc…

cs.LG2021

The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks

Alexander Bastounis, Anders C Hansen, Verner Vlačić

The unprecedented success of deep learning (DL) makes it unchallenged when it comes to classification problems. However, it is well established that the current DL methodology prod…

cs.IT2021

Beurling-type density criteria for system identification

V. Vlačić, C. Aubel, H. Bölcskei

This paper addresses the problem of identifying a linear time-varying (LTV) system characterized by a (possibly infinite) discrete set of delay-Doppler shifts without a lattice (or…

math.CO2019

Neural network identifiability for a family of sigmoidal nonlinearities

Verner Vlačić, Helmut Bölcskei

This paper addresses the following question of neural network identifiability: Does the input-output map realized by a feed-forward neural network with respect to a given nonlinear…