Dust coagulation in equilibrium molecular gas. - Nikolai V. Brilliantov; Frank Spahn (Math. Comput. Simul., 2006)

Anderson acceleration method of finding steady-state particle size distribution for a wide class of aggregation-fragmentation models. - Sergey A. Matveev; V. I. Stadnichuk; E. E. Tyrtyshnikov; Alexander P. Smirnov; N. V. Ampilogova; Nikolai V. Brilliantov (Comput. Phys. Commun., 2018)

Newton method for stationary and quasi-stationary problems for Smoluchowski-type equations. - Ivan V. Timokhin; Sergey A. Matveev; Nana Siddharth; Eugene E. Tyrtyshnikov; Alexander P. Smirnov; Nikolai V. Brilliantov (J. Comput. Phys., 2019)

Aggregation in non-uniform systems with advection and localized source. - Rishat R. Zagidullin; Alexander P. Smirnov; Sergey A. Matveev; Nikolai V. Brilliantov; Pavel L. Krapivsky (CoRR, 2021)

Direct simulation Monte Carlo for new regimes in aggregation-fragmentation kinetics. - Aleksei Kalinov; Alexander Osinsky; Sergey A. Matveev; Wendy Otieno; Nikolai V. Brilliantov (J. Comput. Phys., 2022)

Application of machine learning technique for a fast forecast of aggregation kinetics in space-inhomogeneous systems. - Maria A. Larchenko; Rishat R. Zagidullin; Vladimir V. Palyulin; Nikolai V. Brilliantov (CoRR, 2023)

Knowledge-informed neuro-integrators for aggregation kinetics. - Dmitrii Lukashevich; Ivan Tyukin; Nikolai V. Brilliantov (Commun. Nonlinear Sci. Numer. Simul., 2024)

Umbrella Reinforcement Learning - computationally efficient tool for hard non-linear problems. - Egor E. Nuzhin; Nikolai V. Brilliantov (Commun. Nonlinear Sci. Numer. Simul., 2025)