18 citations · 56 across the 4 of their papers we have counts for
4 papers
CoolMomentum: A Method for Stochastic Optimization by Langevin Dynamics with Simulated Annealing
Oleksandr Borysenko, Maksym Byshkin
Deep learning applications require global optimization of non-convex objective functions, which have multiple local minima. The same problem is often found in physical simulations…
Hybrid Particle-Field Molecular Dynamics Under Constant Pressure
Sigbjørn Løland Bore, Hima Bindu Kolli, Antonio De Nicola +4
Hybrid particle-field methods are computationally efficient approaches for modelling soft matter systems. So far applications of these methodologies have been limited to constant v…
A Simple Algorithm for Scalable Monte Carlo Inference
Alexander Borisenko, Maksym Byshkin, Alessandro Lomi
The methods of statistical physics are widely used for modelling complex networks. Building on the recently proposed Equilibrium Expectation approach, we derive a simple and effici…
Fast Maximum Likelihood estimation via Equilibrium Expectation for Large Network Data
Maksym Byshkin, Alex Stivala, Antonietta Mira +2
A major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macro-structural propertie…