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Modified Hamiltonian Monte Carlo for Bayesian Inference
Radivojevic, T.; Akhmatskaya, E.
(2019-07-22)
(2019-07-22)
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. We show that performance of HMC can be significantly improved by incorporating importance sampling and ...
Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation
(2019-07)
Our inability to predict the behavior of biological systems severely hampers progress in bioengineering and biomedical applications. We cannot predict the effect of genotype changes on phenotype, nor extrapolate the ...
Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models
Zhang, J.; Petersen, S.; Radivojevic, T.; Ramirez, A.; Pérez, A.; Abeliuk, E.; Sánchez, B.; Costello, Z.; Chen, Y.; Fero, M.; Garcia Martin, H.; Nielsen, J.; Keasling, J.; Jensen, M. (2019)
; Abeliuk, E.; Sánchez, B.; Costello, Z.; Chen, Y.; Fero, M.; Garcia Martin, H.; Nielsen, J.; Keasling, J.; Jensen, M. (2019)
In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show ...
Multi-stage splitting integrators for sampling with modified Hamiltonian Monte Carlo methods
Radivojevic, T.; Fernández-Pendás, M.; Sanz-Serna, J.M.; Akhmatskaya, E. (2018-07-17)
(2018-07-17)
Modified Hamiltonian Monte Carlo (MHMC) methods combine the ideas behind two popular sampling approaches: Hamiltonian Monte Carlo (HMC) and importance sampling. As in the HMC case, the bulk of the computational cost of ...
Adaptive Splitting Integrators for Enhancing Sampling Efficiency of Modified Hamiltonian Monte Carlo Methods in Molecular Simulation
Akhmatskaya, E.; Fernández-Pendás, M.; Radivojevic, T.; Sanz-Serna, J.M. (2017-10-24)
; Fernández-Pendás, M.; Radivojevic, T.; Sanz-Serna, J.M. (2017-10-24)
The modified Hamiltonian Monte Carlo (MHMC) methods, i.e., importance sampling methods that use modified Hamiltonians within a Hybrid Monte Carlo (HMC) framework, often outperform in sampling efficiency standard techniques ...
Low-traffic limit and first-passage times for a simple model of the continuous double auction
Scalas, E.; Rapallo, F.; Radivojevic, T. (2017-05)
; Rapallo, F.; Radivojevic, T. (2017-05)
We consider a simplified model of the continuous double auction where prices are integers varying from 1 to $N$ with limit orders and market orders, but quantity per order limited to a single share. For this model, the ...
Enhancing sampling in atomistic simulations of solid state materials for batteries: a focus on olivine NaFePO$_4$
Escribano, B.; Lozano, A.; Radivojevic, T.; Fernández-Pendás, M.; Carrasco, J.; Akhmatskaya, E. (2017-03-07)
(2017-03-07)
The study of ion transport in electrochemically active materials for energy storage systems requires simulations on quantum-, atomistic- and meso-scales. The methods accessing these scales not only have to be effective but ...
Enhancing Sampling in Computational Statistics Using Modified Hamiltonians
(2016-11-15)
The Hamiltonian Monte Carlo (HMC) method has been recognized as a powerful sampling tool in computational statistics. In this thesis, we show that performance of HMC can be dramatically improved by replacing Hamiltonians ...
Wealth distribution and the Lorenz curve: a finitary approach
Scalas, E.; Radivojevic, T.; Garibaldi, U. (2015-12-31)
; Radivojevic, T.; Garibaldi, U. (2015-12-31)
We use three stochastic games for the wealth of economic agents which may be at work in a real economy and we derive their statistical equilibrium distributions. Based on a heuristic argument, we assume that the expected ...
Constant pressure hybrid Monte Carlo simulations in GROMACS
Fernández-Pendás, M.; Escribano, B.; Radivojevic, T.; Akhmatskaya, E. (2014-12-31)
(2014-12-31)
Adaptation and implementation of the Generalized Shadow Hybrid Monte Carlo (GSHMC) method for molecular simulation at constant pressure in the NPT ensemble are discussed. The resulting method, termed NPT-GSHMC, combines ...