Picture for Daniel Kelshaw

Daniel Kelshaw

Computing distances and means on manifolds with a metric-constrained Eikonal approach

Add code
Apr 12, 2024
Viaarxiv icon

Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations

Add code
Feb 01, 2024
Viaarxiv icon

Manifold-augmented Eikonal Equations: Geodesic Distances and Flows on Differentiable Manifolds

Add code
Oct 09, 2023
Viaarxiv icon

Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach

Add code
Jun 19, 2023
Viaarxiv icon

Uncovering solutions from data corrupted by systematic errors: A physics-constrained convolutional neural network approach

Add code
Jun 19, 2023
Viaarxiv icon

Short and Straight: Geodesics on Differentiable Manifolds

Add code
May 24, 2023
Viaarxiv icon

Physics-Informed Convolutional Neural Networks for Corruption Removal on Dynamical Systems

Add code
Nov 07, 2022
Viaarxiv icon

Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems

Add code
Nov 07, 2022
Viaarxiv icon