Computational chemistry on Fujitsu vector-parallel processors: Development and performance of applications software. - Alistair P. Rendell; Andrey A. Bliznyuk; Thomas Huber; Ross H. Nobes; Elena V. Akhmatskaya; Herbert A. Früchtl; Paul W.-C. Kung; Victor Milman; Han Lung (Parallel Comput., 2000)

GSHMC: An efficient method for molecular simulation. - Elena V. Akhmatskaya; Sebastian Reich (J. Comput. Phys., 2008)

A comparison of generalized hybrid Monte Carlo methods with and without momentum flip. - Elena V. Akhmatskaya; Nawaf Bou-Rabee; Sebastian Reich (J. Comput. Phys., 2009)

Erratum to "A comparison of generalized hybrid Monte Carlo methods with and without momentum flip" [J. Comput. Phys 228 (2009) 2256-2265]. - Elena V. Akhmatskaya; Nawaf Bou-Rabee; Sebastian Reich (J. Comput. Phys., 2009)

Extracting S-matrix poles for resonances from numerical scattering data: Type-II Padé reconstruction. - Dmitri Sokolovski; Elena V. Akhmatskaya; S. K. Sen (Comput. Phys. Commun., 2011)

Meso-GSHMC: A stochastic algorithm for meso-scale constant temperature simulations. - Elena V. Akhmatskaya; Sebastian Reich (ICCS, 2011)

Computer Software for Understanding Resonances and Resonance-Related Phenomena in Chemical Reactions. - Dmitri Sokolovski; Elena V. Akhmatskaya (ICCSA (1), 2014)

Numerical Regge pole analysis of resonance structures in elastic, inelastic and reactive state-to-state integral cross sections. - Elena V. Akhmatskaya; Dmitri Sokolovski; C. Echeverría-Arrondo (Comput. Phys. Commun., 2014)

Multiple-time-stepping generalized hybrid Monte Carlo methods. - Bruno Escribano; Elena V. Akhmatskaya; Sebastian Reich; Jon Azpiroz (J. Comput. Phys., 2015)

Adaptive multi-stage integrators for optimal energy conservation in molecular simulations. - Mario Fernández-Pendás; Elena V. Akhmatskaya; Jesús María Sanz-Serna (J. Comput. Phys., 2016)

Multi-stage splitting integrators for sampling with modified Hamiltonian Monte Carlo methods. - Tijana Radivojevic; Mario Fernández-Pendás; Jesús María Sanz-Serna; Elena V. Akhmatskaya (J. Comput. Phys., 2018)

An optimal scaling to computationally tractable dimensionless models: Study of latex particles morphology formation. - Simone Rusconi; Denys Dutykh; Arghir Zarnescu; Dmitri Sokolovski; Elena V. Akhmatskaya (Comput. Phys. Commun., 2020)

Modified Hamiltonian Monte Carlo for Bayesian inference. - Tijana Radivojevic; Elena V. Akhmatskaya (Stat. Comput., 2020)

Numerical Regge pole analysis of resonance structures in state-to-state reactive differential cross sections. - Elena V. Akhmatskaya; Dmitri Sokolovski (Comput. Phys. Commun., 2022)

Reducing model complexity by means of the optimal scaling: Population balance model for latex particles morphology formation. - Simone Rusconi; Christina Schenk; Arghir Zarnescu; Elena V. Akhmatskaya (Appl. Math. Comput., 2023)

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale. - Tyler W. H. Backman; Christina Schenk; Tijana Radivojevic; David Ando; Jahnavi Singh; Jeffrey J. Czajka; Zak Costello; Jay D. Keasling; Yinjie Tang; Elena V. Akhmatskaya; Héctor García Martín (PLoS Comput. Biol., 2023)

Relative frequencies of constrained events in stochastic processes: An analytical approach. - Simone Rusconi; Elena V. Akhmatskaya; Dmitri Sokolovski; N. Ballard; J. C. de la Cal (CoRR, 2024)

Adaptive multi-stage integration schemes for Hamiltonian Monte Carlo. - Lorenzo Nagar; Mario Fernández-Pendás; Jesús María Sanz-Serna; Elena V. Akhmatskaya (J. Comput. Phys., 2024)