60 citations · 215 across the 13 of their papers we have counts for
13 papers
Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: application to planar soft tissues
Ankush Aggarwal, Bjørn Sand Jensen, Sanjay Pant +1
Data-based approaches are promising alternatives to the traditional analytical constitutive models for solid mechanics. Herein, we propose a Gaussian process (GP) based constitutiv…
A Bayesian constitutive model selection framework for biaxial mechanical testing of planar soft tissues: application to porcine aortic valves
Ankush Aggarwal, Luke T. Hudson, Devin W. Laurence +2
A variety of constitutive models have been developed for soft tissue mechanics. However, there is no established criterion to select a suitable model for a specific application. Al…
A holographic study of the characteristics of chaos and correlation in the presence of backreaction
Shankhadeep Chakrabortty, Hironori Hoshino, Sanjay Pant +1
In this work, we perform a holographic study to estimate the effect of backreaction on the correlation between two subsystems forming the thermofield double (TFD) state. Each of th…
Multi-Scale Input Strategies for Medulloblastoma Tumor Classification using Deep Transfer Learning
Marcel Bengs, Satish Pant, Michael Bockmayr +2
Medulloblastoma (MB) is a primary central nervous system tumor and the most common malignant brain cancer among children. Neuropathologists perform microscopic inspection of histop…
Multiscale modelling of reversed Potts shunt as a potential palliative treatment for suprasystemic idiopathic pulmonary artery hypertension in children
Sanjay Pant, Aleksander Sizarov, Angela Knepper1 +4
Reversed Potts shunt (PS) was suggested as palliation for patients with suprasystemic pulmonary arterial hypertension (PAH) and right ventricular (RV) failure. PS, however, can res…
Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database
Gareth Jones, Jim Parr, Perumal Nithiarasu +1
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial…
A physiologically realistic virtual patient database for the study of arterial haemodynamics
Gareth Jones, Jim Parr, Perumal Nithiarasu +1
This study creates a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the affects of arterial d…
A proof of concept study for machine learning application to stenosis detection
Gareth Jones, Jim Parr, Perumal Nithiarasu +1
This proof of concept (PoC) assesses the ability of machine learning (ML) classifiers to predict the presence of a stenosis in a three vessel arterial system consisting of the abdo…
Effect of back reaction on entanglement and subregion volume complexity in strongly coupled plasma
Shankhadeep Chakrabortty, Sanjay Pant, Karunava Sil
The back reaction imparted by a uniform distribution of heavy static fundamental quarks on large strongly coupled gauge theory can be holographically realized as a deformatio…
Beyond Newton: a new root-finding fixed-point iteration for nonlinear equations
Ankush Aggarwal, Sanjay Pant
Finding roots of equations is at the heart of most computational science. A well-known and widely used iterative algorithm is the Newton's method. However, its convergence depends…
On improving the numerical convergence of highly nonlinear elasticity problems
Yue Mei, Daniel E. Hurtado, Sanjay Pant +1
Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving…
Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems
Sanjay Pant
A new class of functions, called the `Information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a…
A non-parametric k-nearest neighbour entropy estimator
Damiano Lombardi, Sanjay Pant
A non-parametric k-nearest neighbour based entropy estimator is proposed. It improves on the classical Kozachenko-Leonenko estimator by considering non-uniform probability densitie…