Search Results for author:
Found 14 papers, 7 papers with code
Bayesian Inference of Stochastic Dynamical Networks
Given that usually only a partial set of nodes are able to observe, in this paper, we consider linear CT systems to depict networks since they can model unmeasured nodes via transfer functions.
A Sampling Theorem for Exact Identification of Continuous-time Nonlinear Dynamical Systems
The necessary and sufficient condition is proposed -- which is built from Koopman operator -- to the exact identification of the CT system from sampled data.
DBSegment: Fast and robust segmentation of deep brain structures -- Evaluation of transportability across acquisition domains
We trained the network to segment 30 deep brain structures, as well as a brain mask, using labels generated from a registration-based approach.
CrowdCog: A Cognitive Skill based System for Heterogeneous Task Assignment and Recommendation in Crowdsourcing
While crowd workers typically complete a variety of tasks in crowdsourcing platforms, there is no widely accepted method to successfully match workers to different types of tasks.
Machine Discovery of Partial Differential Equations from Spatiotemporal Data
The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data.
Data-driven Discovery of Cyber-Physical Systems
Cyber-physical systems (CPSs) embed software into the physical world.
Continuous time Gaussian process dynamical models in gene regulatory network inference
BINGO is based on MCMC sampling of trajectories of the GPDM and estimating the hyperparameters of the covariance function of the Gaussian process.
Optimization and Control Statistics Theory Molecular Networks Statistics Theory
Synchronisation of Partial Multi-Matchings via Non-negative Factorisations
In order to deal with the inherent non-convexity of the permutation synchronisation problem, we use an initialisation procedure based on a novel rotation scheme applied to the solution of the spectral relaxation.
Bayesian variable selection in linear dynamical systems
In biological applications, the typical problem is that the sampling frequency is low, and consequentially the system identification problem is ill-posed.
Methodology Optimization and Control Quantitative Methods
Distributed methods for synchronization of orthogonal matrices over graphs
This paper addresses the problem of synchronizing orthogonal matrices over directed graphs.
Shape-aware Surface Reconstruction from Sparse 3D Point-Clouds
Estimating the parameters of the GMM in a maximum a posteriori manner yields the reconstruction of the surface from the given data points.
Linear Shape Deformation Models with Local Support Using Graph-based Structured Matrix Factorisation
Representing 3D shape deformations by linear models in high-dimensional space has many applications in computer vision and medical imaging, such as shape-based interpolation or segmentation.
On Transitive Consistency for Linear Invertible Transformations between Euclidean Coordinate Systems
Two direct or centralized synchronization methods are presented for different graph topologies; the first one for quasi-strongly connected graphs, and the second one for connected graphs.
A Solution for Multi-Alignment by Transformation Synchronisation
Simulations demonstrate that for noisy transformations, a large proportion of missing data and even for wrong correspondence assignments the method delivers encouraging results.
