Search Results for author:
Found 7 papers, 1 papers with code
Rare Events Analysis and Computation for Stochastic Evolution of Bacterial Populations
In this paper, we develop a computational approach for computing most likely trajectories describing rare events that correspond to the emergence of non-dominant genotypes.
Automatic classification of deformable shapes
Let $\mathcal{D}$ be a dataset of smooth 3D-surfaces, partitioned into disjoint classes $\mathit{CL}_j$, $j= 1, \ldots, k$.
Stochastic Neural Networks for Automatic Cell Tracking in Microscopy Image Sequences of Bacterial Colonies
Our initial tests using experimental image sequences (i. e., real data) of E. coli colonies also yield convincing results, with a registration accuracy ranging from 90% to 100%.
Pattern recognition in micro-trading behaviors before stock price jumps: A framework based on multivariate time series analysis
The individual and joint informativeness levels of the attributes in predicting price jumps are evaluated and compared.
Predicting intraday jumps in stock prices using liquidity measures and technical indicators
The result provides initial evidence of the predictability of jump arrivals and jump directions using level-2 stock data as well as the effectiveness of using a combination of liquidity measures and technical indicators in this prediction.
Realized volatility and parametric estimation of Heston SDEs
We present a detailed analysis of \emph{observable} moments based parameter estimators for the Heston SDEs jointly driving the rate of returns $R_t$ and the squared volatilities $V_t$.
Markov Random Fields and Mass Spectra Discrimination
We also outline the successful tests of our approach to generate efficient explicit signatures for six benchmark discrimination tasks, based on mass spectra acquired from colorectal cancer patients, as well as from ovarian cancer patients.
