3 papers
cs.NE2026
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…
cond-mat.mtrl-sci2026
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…
physics.gen-ph2025
The Quantum Memory Matrix: A Unified Framework for the Black Hole Information Paradox
Florian Neukart, Reuben Brasher, Eike Marx
We present the Quantum Memory Matrix (QMM) hypothesis, which addresses the longstanding Black Hole Information Paradox rooted in the apparent conflict between Quantum Mechanics (QM…