space-time

Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors

Anonymous Multi-Agent Path Finding (MAPF) with Conflict-Based Search and Space-Time A*

rFIA

Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the temporal part of the space-time process while, standard GP regression is used for the spatial part

SAE Unit/area Models and Methods for Estimation in R

Some teaching materials about MIMO in Communications.

Software package for Gaussian Process (GP) modelling written in R language. The core functions are coded in C++ and based on the EIGEN library (through RcppEigen).

Space-Time Discontinuous Galerkin Code implemented for final project in graduate course TAM 574 - Advanced Finite Element Methods

olli-scripts: Dieter (Olli) Egger's REDUCE/Symbolic scripts, used as demonstrations for Symbolic (as shown in the screenshots on Google Play), and relating to Dieter's research in curved space-time, with scientific background papers, automatically mirrored from https://reduce-algebra.sourceforge.io/tutorials/EggerScripts.en.php

d-stem-LUR: Companion repository for the paper entitled "Concurrent spatiotemporal daily land use regression modeling and missing data imputation of fine particulate matter using distributed space-time expectation maximization", GitHub, 2019. The paper is published in the Atmospheric Environment journal

Newcastle University Group Project - Routes

This is the code that supplements arXiv:2009.08875, where we describe a parallel algorithm for solving linear parabolic equations.

STooDs is a framework to build and estimate probabilistic models for data varying in Space, Time or other Dimensions.

This code supplements arXiv:2108.03055, where we describe an adaptive boundary element method for the heat equation.

This code is a modification of MFEM, a C++ library for finite element methods. The modification includes: 4D meshes and finite elements, multigrid and time-slabbing solvers and a natural setting for considering (constrained) first-order system least-squares formulations.