Training Randomly Connected, Recurrent Artificial Neural Networks Using PSO. - Vytautas Jancauskas (ANTS Conference, 2010)

On Multi-Objective Optimization Aided Visualization of Graphs Related to Business Process Diagrams. - Vytautas Jancauskas; Giedrius Kaukas; Antanas Zilinskas; Julius Zilinskas (DB&Local Proceedings, 2012)

On the Multi-objective Optimization Aided Drawing of Connectors for Graphs Related to Business Process Management. - Vytautas Jancauskas; Ausra Mackute-Varoneckiene; Audrius Varoneckas; Antanas Zilinskas (ICIST, 2012)

Optimizing Neighbourhood Distances for a Variant of Fully-Informed Particle Swarm Algorithm. - Vytautas Jancauskas (NICSO, 2013)

Introducing VECMAtk - Verification, Validation and Uncertainty Quantification for Multiscale and HPC Simulations. - Derek Groen; Robin A. Richardson; David W. Wright 001; Vytautas Jancauskas; Robert Sinclair; Paul Karlshoefer; Maxime Vassaux; Hamid Arabnejad; Tomasz Piontek; Piotr Kopta; Bartosz Bosak; Jalal Lakhlili; et al. (ICCS (4), 2019)

Patterns for High Performance Multiscale Computing. - Saad Alowayyed; Tomasz Piontek; James L. Suter; Olivier Hoenen; Derek Groen; Onnie Luk; Bartosz Bosak; Piotr Kopta; Krzysztof Kurowski; Oliver Perks; Keeran Brabazon; Vytautas Jancauskas; et al. (Future Gener. Comput. Syst., 2019)

VECMAtk: A Scalable Verification, Validation and Uncertainty Quantification Toolkit for Scientific Simulations. - Derek Groen; Hamid Arabnejad; Vytautas Jancauskas; Wouter Edeling; Fredrik Jansson; Robin A. Richardson; Jalal Lakhlili; Linda van Veen; Bartosz Bosak; Piotr Kopta; D. W. Wright; Nicolas Monnier; et al. (CoRR, 2020)

Tutorial applications for Verification, Validation and Uncertainty Quantification using VECMA toolkit. - Diana Suleimenova; Hamid Arabnejad; Wouter Edeling; David Coster; Onnie O. Luk; Jalal Lakhlili; Vytautas Jancauskas; Michal Kulczewski; Lourens E. Veen; Dongwei Ye; Pavel Zun; Valeria V. Krzhizhanovskaya; et al. (J. Comput. Sci., 2021)

Lightning UQ Box: A Comprehensive Framework for Uncertainty Quantification in Deep Learning. - Nils Lehmann; Jakob Gawlikowski; Adam J. Stewart; Vytautas Jancauskas; Stefan Depeweg; Eric T. Nalisnick; Nina Maria Gottschling (CoRR, 2024)