1 citations · 1 across the 3 of their papers we have counts for
3 papers
LLM-Driven Evolutionary Generation of Multi-Objective Bayesian Optimization Algorithms
Georgios Laskaris, Reuben Brasher, Niki van Stein +3
Designing effective multi-objective Bayesian optimization (MOBO) algorithms requires balancing many interdependent design choices whose optimal configuration is problem-dependent a…
Multi-objective optimization and quantum hybridization of equivariant deep learning interatomic potentials
G. Laskaris, D. Morozov, D. Tarpanov +6
Allegro is a machine learning interatomic potential model designed to predict atomic properties in molecules using E(3) equivariant neural networks. When training this model, there…
Comparison between Tensor Networks and Variational Quantum Classifier
Georgios Laskaris, Artem A. Melnikov, Michael R. Perelshtein +3
The primary objective of this paper is to conduct a comparative analysis between two Machine Learning approaches: Tensor Networks (TN) and Variational Quantum Classifiers (VQC). Wh…