Publications (6)
Constrained Empirical Risk Minimization: Theory and Practice
Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke +1
Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions. This flexibility, however, makes the strict enforcement of cons…
Model-based Dynamic 3D MRI Reconstructions using Neural Fields and Tensor Product Expansions
Ray Sheombarsing, Max van Riel, David Heesterbeek +2
Conventional MRI reconstruction methods treat images and coil sensitivities as discrete objects, leading to high memory demands and limited structural awareness that hamper effecti…
Validated integration of semilinear parabolic PDEs
Jan Bouwe van den Berg, Maxime Breden, Ray Sheombarsing
Integrating evolutionary partial differential equations (PDEs) is an essential ingredient for studying the dynamics of the solutions. Indeed, simulations are at the core of scienti…
Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation Algorithms
Joren Brunekreef, Eric Marcus, Ray Sheombarsing +2
Image segmentation algorithms can be understood as a collection of pixel classifiers, for which the outcomes of nearby pixels are correlated. Classifier models can be calibrated us…
Validated computations for connecting orbits in polynomial vector fields
Jan Bouwe van den Berg, Ray Sheombarsing
In this paper we present a computer-assisted procedure for proving the existence of transverse heteroclinic orbits connecting hyperbolic equilibria of polynomial vector fields. The…
Subpixel object segmentation using wavelets and multi resolution analysis
Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke +1
We propose a novel deep learning framework for fast prediction of boundaries of two-dimensional simply connected domains using wavelets and Multi Resolution Analysis (MRA). The bou…