InCantor’s ParadisebyCaroline ArnoldClimate Modeling Across ScalesSmall but important: including subgrid-scale processes in climate and weather modelsSep 18, 20231Sep 18, 20231
InLevel Up CodingbyPhilip MoczCreate Your Own Riemann Solver (With Python)In today’s recreational coding exercise, we create an exact Riemann Solver for the Euler equations. The solver finds the solution for the…Aug 13, 20231Aug 13, 20231
InBetter ProgrammingbyCallum BruceExploring the Intersection of AI and Physics: The Role of ChatGPT in Code GenerationAnalyzing the strength and weaknesses of ChatGPT in solving Physics-based problemsMar 13, 20232Mar 13, 20232
InLevel Up CodingbyPhilip MoczCreate Your Own Navier-Stokes Spectral Method Fluid Simulation (With Python)For today’s recreational coding exercise, we solve the Navier-Stokes equations for an incompressible viscous fluid. To do so, we will…Aug 4, 20237Aug 4, 20237
InTDS ArchivebyCallum BrucePID Controller Optimization: A Gradient Descent ApproachUsing machine learning to solve engineering optimization problemsAug 1, 20232Aug 1, 20232
InTDS ArchivebyHennie de HarderOptimizing Connections: Mathematical Optimization within GraphsAn introduction to graph theory and its applicationsJul 28, 20235Jul 28, 20235
InTDS ArchivebyShuai GuoUsing Monte Carlo to quantify the model prediction errorMonte Carlo simulations demonstratedOct 17, 20201Oct 17, 20201
InTDS ArchivebyShuai GuoUncertainty Visualization Made Easy With Hypothetical Outcome PlotsUse animations to present the uncertainty vividly.Dec 23, 2020Dec 23, 2020
InTDS ArchivebyShuai GuoPerforming Uncertainty Analysis In Three Steps: A Hands-on GuideThis post will walk you through a complete uncertainty analysis case study using Latin Hypercube sampling, Monte Carlo simulation, and…Jan 13, 20212Jan 13, 20212
InTDS ArchivebyShuai GuoUncertainty Quantification ExplainedA practice for making reliable model-based predictionsJul 20, 20202Jul 20, 20202
InTDS ArchivebyShuai GuoAn introduction to surrogate modeling, Part I: fundamentalsA machine learning approach to accelerate engineering designOct 29, 20201Oct 29, 20201
InTDS ArchivebyShuai GuoUnraveling the Design Pattern of Physics-Informed Neural Networks: Part 07Active learning for efficiently training parametric PINNJul 25, 2023Jul 25, 2023
InTDS ArchivebyShuai GuoDiscovering Differential Equations with Physics-Informed Neural Networks and Symbolic RegressionA case study with step-by-step code implementationJul 28, 20237Jul 28, 20237
InTDS ArchivebyFrançois PorcherA Gentle Introduction to Bayesian Deep LearningExplore the intersection of Bayesian statistics and Deep Learning, its advantages and limitations in this easy guideJul 26, 20235Jul 26, 20235
InTDS ArchivebyShuai GuoSolving Inverse Problems With Physics-Informed DeepONet: A Practical Guide With Code ImplementationTwo case studies with parameter estimation and input function calibrationJul 17, 20233Jul 17, 20233
InTDS ArchivebyShuai GuoOperator Learning via Physics-Informed DeepONet: Let’s Implement It From ScratchA deep dive into the DeepONets, physics-informed neural networks, and physics-informed DeepONetsJul 7, 20234Jul 7, 20234
InTDS ArchivebyAlbers UzilaComplete Step-by-step Particle Swarm Optimization Algorithm from ScratchAnd its implementation for solving a nonlinear control theory problemApr 4, 20221Apr 4, 20221
InIntuitionbyMathcube15 Lines of Python: Poisson’s Equation in N DimensionsUse Python magic to solve the Poisson equation in any number of dimensionsMar 23, 20221Mar 23, 20221
InTDS ArchivebyRobert KwiatkowskiMonte Carlo Simulation — a practical guideA versatile method for parameters estimation. Exemplary implementation in Python programming language.Jan 31, 20228Jan 31, 20228
InTDS ArchivebyDarío WeitzMonte Carlo SimulationPart 3: Histograms & Density PlotsAug 30, 2022Aug 30, 2022