activity
20222026
most citedOgden Material Calibration via Magnetic Resonance Cartography, Parameter Sensitivity, and Variational System Identification

12 citations · 13 across the 8 of their papers we have counts for

collaborators

9 papers

quant-ph2026

Resource Analysis for Quantum Simulation of Spatially Varying Transport-Reaction Equations

Benjamin Jasperson, Krishna Garikipati, Siddhartha Srivastava

Spatially varying coefficients are the primary source of circuit complexity in quantum simulation of linear advection-diffusion-reaction equations. This work presents a resource an…

cs.LG2026

On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks

Pharindra Pathak, Vipin Kumar, Trenton M. Ricks +2

Short-fiber thermoplastic (SFT) composites are increasingly employed in lightweight aerospace and automotive structures owing to their favorable strength-to-weight ratio, high prod…

cs.CE2026

Bayesian Variational System Identification with Weak-Form Residual Likelihoods

Chengyang Huang, Siddhartha Srivastava, Krishna Garikipati +1

We consider system identification for discovering parameterized operators in governing partial differential equations (PDEs) from noisy spatiotemporal data. Building on variational…

physics.bio-ph2026

Constitutive parameter inference using physics-based data-driven modeling in full volume datasets of intact and torn rotator cuff tendons

Carla Nathaly Villacís Núñez, Siddhartha Srivastava, Ulrich Scheven +3

In this work, we characterized the material properties of an animal model of the rotator cuff tendon using full volume datasets of both its intact and injured states by capturing i…

cond-mat.mtrl-sci2025

Equivariant graph neural network surrogates for predicting the properties of relaxed atomic configurations

Jamie Holber, Siddhartha Srivastava, Krishna Garikipati

Density functional theory (DFT) calculations determine the relaxed atomic positions and lattice parameters that minimize the formation energy of a structure. We present an equivari…

cond-mat.mtrl-sci2025

Inference of phase field fracture models

Elizabeth Livingston, Siddhartha Srivastava, Jamie Holber +2

The phase field approach to modeling fracture uses a diffuse damage field to represent a crack. This addresses the singularities that arise at the crack tip in computations with sh…

q-bio.QM2023

Pattern formation in dense populations studied by inference of nonlinear diffusion-reaction mechanisms

Siddhartha Srivastava, Krishna Garikipati

Reaction-diffusion systems have been proposed as a model for pattern formation and morphogenesis. The Fickian diffusion typically employed in these constructions model the Brownian…

math.NA2022★ 1 cited

Numerical analysis of non-local calculus on finite weighted graphs, with application to reduced-order modelling of dynamical systems

Matthew Duschenes, Siddhartha Srivastava, Krishna Garikipati

We present an approach to reduced-order modelling that builds off recent graph-theoretic work for representation, exploration, and analysis of computed states of physical systems (…

cond-mat.soft2022★ 12 cited

Ogden Material Calibration via Magnetic Resonance Cartography, Parameter Sensitivity, and Variational System Identification

Denislav P. Nikolov, Siddartha Srivastava, Bachir A. Abeid +4

Contemporary material characterisation techniques that leverage deformation fields and the weak form of the equilibrium equations face challenges in the numerical solution procedur…