Deep Ray

Orcid: 0000-0002-8460-9862

According to our database1, Deep Ray authored at least 26 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Probabilistic Brain Extraction in MR Images via Conditional Generative Adversarial Networks.
IEEE Trans. Medical Imaging, March, 2024

Learning WENO for entropy stable schemes to solve conservation laws.
CoRR, 2024

2023
A dimension-reduced variational approach for solving physics-based inverse problems using generative adversarial network priors and normalizing flows.
CoRR, 2023

Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts.
CoRR, 2023

Learning end-to-end inversion of circular Radon transforms in the partial radial setup.
CoRR, 2023

Solution of physics-based inverse problems using conditional generative adversarial networks with full gradient penalty.
CoRR, 2023

Deep Learning and Computational Physics (Lecture Notes).
CoRR, 2023

2022
A pressure-correction and bound-preserving discretization of the phase-field method for variable density two-phase flows.
J. Comput. Phys., 2022

Probabilistic medical image imputation via deep adversarial learning.
Eng. Comput., 2022

Variationally Mimetic Operator Networks.
CoRR, 2022

The efficacy and generalizability of conditional GANs for posterior inference in physics-based inverse problems.
CoRR, 2022

2021
Multilevel Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data.
SIAM/ASA J. Uncertain. Quantification, 2021

Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks.
J. Comput. Phys., 2021

Solution of Physics-based Bayesian Inverse Problems with Deep Generative Priors.
CoRR, 2021

2020
Constraint-aware neural networks for Riemann problems.
J. Comput. Phys., 2020

Deep learning observables in computational fluid dynamics.
J. Comput. Phys., 2020

Controlling oscillations in high-order Discontinuous Galerkin schemes using artificial viscosity tuned by neural networks.
J. Comput. Phys., 2020

A discontinuous Galerkin method for a diffuse-interface model of immiscible two-phase flows with soluble surfactant.
CoRR, 2020

Multi-level Monte Carlo Finite Difference Methods for Fractional Conservation Laws with Random Data.
CoRR, 2020

Iterative Surrogate Model Optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks.
CoRR, 2020

2019
Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem.
J. Comput. Phys., 2019

Detecting troubled-cells on two-dimensional unstructured grids using a neural network.
J. Comput. Phys., 2019

On the approximation of rough functions with deep neural networks.
CoRR, 2019

2018
An artificial neural network as a troubled-cell indicator.
J. Comput. Phys., 2018

2017
An entropy stable finite volume scheme for the two dimensional Navier-Stokes equations on triangular grids.
Appl. Math. Comput., 2017

2016
A Sign Preserving WENO Reconstruction Method.
J. Sci. Comput., 2016


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