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PinnDE: A Python library for solving differential equations with physics informed neural networks and deep operator networks
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
About Code release for “RoPINN: Region Optimized Physics-Informed Neural Networks” (NeurIPS 2024), https://arxiv.org/abs/2405.14369
Neural network based solvers for partial differential equations and inverse problems 🌌. Implementation of physics-informed neural networks in pytorch.
Software for the paper "Performance of affine-splitting pseudo-spectral methods for fractional complex Ginzburg-Landau equations"
A library for scientific machine learning and physics-informed learning
Lugiato-Lefever Equation Solver
Python package for temporal evolution of initial conditions under the generalized Lugiato-Lefever equation
Matlab implementation of particle swarm optimization. Well documented with examples.
This repository displays the demos of some Intelligent Optimization Algorithms, including SA (Simulated Annealing), GA (Genetic algorithm), PSO (Particle Swarm Optimizer) and so on. And some other …
Decomposition Based Multi-Objective Particle Swarm Optimization
This is the shared package to simulate pulse propagation in a fiber with GMMNLSE/MM-UPPE or bulk material with 3D-UPPE
Official Code for DragGAN (SIGGRAPH 2023)
Simulation for propagating ultrashort laser pulses in freespace or in a gas-filled capillary
Ultrashort optical pulse propagation in terms of forward models for the analytic signal
Clapeyron provides a framework for the development and use of fluid-thermodynamic models, including SAFT, cubic, activity, multi-parameter, and COSMO-SAC.
Graphical application for simulating Kerr frequency combs using both the Lugiato-Lefever equation and an Ikeda map.