In this paper, we revisit the recently established theoretical guarantees for the convergence of the Langevin Monte Carlo algorithm of sampling from a smooth and (strongly) log-concave density. We improve the existing results when the convergence is measured in the Wasserstein distance and provide further insights on the very tight relations between, on the one hand, the Langevin Monte Carlo fo...

This paper describes a suite of optimization tools for radiation treatment planning within the Matlab programming environment. The data included with these tools was computed for real patient cases using a Monte Carlo dose engine. The formulation of a series of optimization models is described that utilizes this data within a modeling system. Furthermore, visualization techniques are provided t...

The REBUS-3 burnup code, used in the ANL RERTR Program, is a very general code that uses diffusion theory (DIF3D) to obtain the fluxes required for reactor burnup analyses. Diffusion theory works well for most reactors. However, to include the effects of exact geometry and strong absorbers that are difficult to model using diffusion theory, a Monte Carlo method is required. MCNP, “a general-pur...

We present a method for controlling the output of procedural modeling programs using Sequential Monte Carlo (SMC). Previous probabilistic methods for controlling procedural models use Markov Chain Monte Carlo (MCMC), which receives control feedback only for completely-generated models. In contrast, SMC receives feedback incrementally on incomplete models, allowing it to reallocate computational...

We present a first application of a previously published method for the computation of QCD processes that is accurate at next-to-leading order, and that can be interfaced consistently to standard shower Monte Carlo programs. We have considered Z pair production in hadron-hadron collisions, a process whose complexity is sufficient to test the general applicability of the method. We have interfac...

In this paper we apply a Monte-Carlo Tree Search implementation that is boosted with domain knowledge to the game of poker. More specifically, we integrate an opponent model in the Monte-Carlo Tree Search algorithm to produce a strong poker playing program. Opponent models allow the search algorithm to focus on relevant parts of the game-tree. We use an opponent modelling approach that starts f...

In this paper, we propose new deterministic interpolation algorithms and Monte Carlo interpolation algorithms for sparse multivariate polynomials represented by straight-line programs. Let f be an n-variate polynomial with a degree bound D and and term bound T . Our deterministic algorithms have better complexities than existing deterministic interpolation algorithms in most cases. Our Monte Ca...

We suggest a method implemented in a computer program, immodestly dubbed TSUNAMI, that allows us to compare two homologous protein subfamilies with respect to the distribution of substitution rates along sequences. This study furthers our earlier work on a wavelet model of rate variation (1). The current approach allows sensitive detection of subtle discordances in the selection patterns betwee...

This study proposes a new method to quantitatively represent the uncertainty existing in open pit optimization results due to variations in mineral prices. After generating multiple mineral prices using Monte Carlo simulation with data on past mineral prices, a probability model that represents the uncertainty was developed by integrating multiple open pit optimization results derived from the ...