Recent clinical trials have shown that adaptive drug therapies can be more efficient than a
standard cancer treatment based on a continuous use of maximum tolerated doses (MTD) …

Abstract The Laplace-Beltrami operator (LBO) emerges from studying manifolds equipped
with a Riemannian metric. It is often called the swiss army knife of geometry processing as it …

We introduce a modification of the fast-marching algorithm, which solves the anisotropic
eikonal equation associated to an arbitrary continuous Riemannian metric \calM on a two-or …

We present a PDE-based approach for finding optimal paths for the Reeds–Shepp car. In
our model we minimize a (data-driven) functional involving both curvature and length …

In this paper, we introduce an efficient method for computing curves minimizing a variant of
the Euler–Mumford elastica energy, with fixed endpoints and tangents at these endpoints …

In this paper, we propose a novel curvature penalized minimal path model via an orientation-
lifted Finsler metric and the Euler elastica curve. The original minimal path model computes …

We introduce numerical schemes for computing distances and shortest paths with respect to
several planar paths models, featuring curvature penalization and data-driven velocity: the …

We introduce a novel discretization of the Monge-Ampère operator, simultaneously
consistent and degenerate elliptic, hence accurate and robust in applications. These …

We introduce a generalized Fast-Marching algorithm, able to compute paths globally
minimizing a measure of length, defined with respect to a variety of metrics in dimension two …

We introduce a new discretization scheme for Anisotropic Diffusion, AD-LBR, on two and
three dimensional Cartesian grids. The main features of this scheme is that it is non-negative …