3 citations · 9 across the 5 of their papers we have counts for
5 papers
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approach
Vinicius V. Santana, Erbet Costa, Carine M. Rebello +3
This study presents a systematic machine learning approach for creating efficient hybrid models and discovering sorption uptake models in non-linear advection-diffusion-sorption sy…
A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas
Mohamed Tarek, Jose Storopoli, Casey Davis +4
This paper provides a comprehensive tutorial for Bayesian practitioners in pharmacometrics using Pumas workflows. We start by giving a brief motivation of Bayesian inference for ph…
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed!
Avik Pal, Alan Edelman, Chris Rackauckas
Implicit layer deep learning techniques, like Neural Differential Equations, have become an important modeling framework due to their ability to adapt to new problems automatically…
DelayDiffEq: Generating Delay Differential Equation Solvers via Recursive Embedding of Ordinary Differential Equation Solvers
David Widmann, Chris Rackauckas
Traditional solvers for delay differential equations (DDEs) are designed around only a single method and do not effectively use the infrastructure of their more-developed ordinary…
Parallelizing Explicit and Implicit Extrapolation Methods for Ordinary Differential Equations
Utkarsh, Chris Elrod, Yingbo Ma +1
Numerically solving ordinary differential equations (ODEs) is a naturally serial process and as a result the vast majority of ODE solver software are serial. In this manuscript we…