Publications

Journal Publications

T. Anandh, D. Ghose, S. Ganesan
FastVPINNs: An efficient tensor-based Python library for solving partial differential equations using hp-Variational Physics Informed Neural Networks.
Journal of Open Source Software (JOSS), 2024, 9(99), 6764.

T. Anandh, D. Ghose, H. Jain, S. Ganesan
FastVPINNs: Tensor-Driven Acceleration of VPINNs for Complex Geometries.
(2024) arXiv:2404.12063.

S. Yadav, S. Ganesan
ConvStabNet: A CNN-based approach for the prediction of local stabilization parameter for SUPG scheme.
(2024) Calcolo (accepted).

S. Yadav, S. Ganesan
Artificial Neural Network-augmented stabilized finite element method.
Journal of Computational Physics (2024), 499, 112702.

S. Ganesan, M. K. Singh
Operator-splitting finite element method for solving the radiative transfer equation.
Numerical Algorithms (2024).

D. Garg, S. Ganesan
Local projection stabilized finite element methods for advection–reaction problems.
Calcolo (2023) 60, Article number: 45.

S. Srivastava, S. Ganesan
A stabilized local projection finite element approximation for computations of Oldroyd-B viscoelastic fluid flows.
Int J Adv Eng Sci Appl Math, (2022), 13, 383–393.

D. Garg, S. Ganesan
Generalized local projection stabilized nonconforming finite element methods for Darcy equations.
Numerical Algorithms, (2022) 89, 341-369.

D. Garg, S. Ganesan
An overlapping local projection stabilization for Galerkin approximations of Stokes and Darcy flow problems.
Applied Numerical Mathematics, (2022), 171, 106-127.

S. Ganesan, D. Subramani, T. Anandh, D. Ghose, GR. Babu
Ensemble forecast of COVID-19 in Karnataka for vulnerability assessment and policy interventions.
(2021) medRxiv

S.M. Joshi, T. Anandh, B. Teja, S. Ganesan
On the choice of hyper-parameters of artificial neural networks for stabilized finite element schemes.
Int J Adv Eng Sci Appl Math (2021), 13, 278–297.

S. Ganesan, D. Subramani
Spatio-temporal predictive modeling framework for infectious disease spread.
(2021), Nature Scientific Reports 11, 6741.

B. Pal, S. Ganesan
An a priori error analysis for a projection based variational multiscale finite element method for Oseen problems in a time-dependent domain.
Comput. Math. with Appl., (2021), 82, 130-147.

Conference Presentations

Divij Ghose, Thivin Anandh, Sashikumaar Ganesan
FastVPINNs: A fast, versatile and robust Variational PINNs framework for forward and inverse problems in science
ICLR 2024 Workshop on AI4DifferentialEquations In Science

Thivin Anandh, Divij Ghose, Sashikumaar Ganesan
Fast and Efficient hp-Variational PINNs framework for solving the Incompressible Navier-Stokes equations
Twelfth International Conference on Computational Fluid Dynamics (ICCFD12), Kobe, Japan, July 14-19, 2024

Thivin Anandh, Sashikumaar Ganesan
GPU ACCELERATED FEM BASED LAGRANGIAN PARTICLE TRACKING FRAMEWORK FOR HUMAN AIR PATHWAY
ParCFD2024 35th International Conference on Parallel Computational Fluid Dynamics, Bonn, Germany, Sep 02-04 2024

Divij Ghose, Thivin Anandh, Deepak Subramani, Sashikumaar Ganesan
Stochastic Dynamically orthogonal field equations: Finite Element Algorithms and implementations
LACAM-2024, IISer TVM, Feb-2024

Mahesh Tom, Sashikumaar Ganesan
An approach for quantifying errors due to initial condition uncertainty in Physics informed neural networks using auto Encoders
LACAM-2024, IISer

Thivin Anandh, Divij Ghose, Himanshu Jain, Sashikumaar Ganesan
CRUNCH Seminar: FastVPINNS: Tensor-Driven Acceleration Of VPINNS For Complex Geometries
CRUNCH Seminar

Subodh M. Joshi, Thivin Anandh, Sashikumaar Ganesan
A Deep learning framework coupled with reduced order modelling for real time monitoring of fluid flows
EECS 2023