Kinetic. jl is a lightweight finite volume toolbox written in the Julia programming language for
the study of computational physics and scientific machine learning. It is an open-source …

1. Introduction. In this report a review of Neural Ordinary Differential Equations (Neural
ODEs), as well as an implementation coded in Julia, is presented. Neural ODEs are a class of …

Particle-In-Cell (PIC) methods are frequently used for kinetic, high-fidelity simulations of
plasmas. Implicit formulations of PIC algorithms feature strong conservation properties, up to …

… 2018). We note that discrete adjoints are known to be more stable than continuous adjoints
(Zhang & Sandu, 2014) and in the context of neural ODEs have been shown to stabilize the …

Modern tools in optics allow for generation of laser beams with essentially arbitrary intensity
patterns. However, in practice doing so requires solution of a computationally intensive …

Dicrotic Notch (DN) is a distinctive and clinically significant feature of the arterial blood
pressure curve. Its automatic identification has been the focus of many kinds of research using …

In this paper, we present RayTracer.jl, a renderer in Julia that is fully differentiable using
source-to-source Automatic Differentiation (AD). This means that RayTracer not only renders 2D …

… The core task is to pre-identify the target nodes whose operators are non-transpose-commutative …
2018. A general reinforcement learning algorithm that masters chess, shogi, and Go …

View Video Presentation: https://doi.org/10.2514/6.2022-1441.vid In this paper, we seek to
estimate the invariant sets of stochastic dynamical systems by solving the steady-state form of …