1 citations · 2 across the 4 of their papers we have counts for
4 papers
Improving Accuracy and Efficiency of Implicit Neural Representations: Making SIREN a WINNER
Hemanth Chandravamsi, Dhanush V. Shenoy, Steven H. Frankel
We identify and address a fundamental limitation of sinusoidal representation networks (SIRENs), a class of implicit neural representations. SIRENs Sitzmann et al. (2020), when not…
Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stocks
Joao Felipe Gueiros, Hemanth Chandravamsi, Steven H. Frankel
This paper explores the use of deep residual networks for pricing European options on Petrobras, one of the world's largest oil and gas producers, and compares its performance with…
PINNs for Solving Unsteady Maxwell's Equations: Convergence Issues and Comparative Assessment with Compact Schemes
Gal G. Shaviner, Hemanth Chandravamsi, Shimon Pisnoy +2
Physics-Informed Neural Networks (PINNs) have recently emerged as a promising alternative for solving partial differential equations, offering a mesh-free framework that incorporat…
On the Application of Gradient Based Reconstruction for Flow Simulations on Generalized Curvilinear and Dynamic Mesh Domains
Hemanth Chandravamsi, Amareshwara Sainadh Chamarthi, Natan Hoffmann +1
Accurate high-speed flow simulations of practical interest require numerical methods with high-resolution properties. In this paper, we present an extension and demonstration of th…