☆73Nov 15, 2022Updated 3 years ago
Alternatives and similar repositories for relative_balancing
Users that are interested in relative_balancing are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆30May 8, 2023Updated 3 years ago
- ☆17Jun 6, 2023Updated 3 years ago
- Official code for DPM : A Novel Training Method for Physics-Informed Neural Networks in Extrapolation☆10Nov 2, 2021Updated 4 years ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆107Oct 24, 2022Updated 3 years ago
- Accompanyig code for "Training Physics-Informed Neural Networks: one learning to rule them all?"☆13Nov 15, 2022Updated 3 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ☆265Oct 14, 2021Updated 4 years ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆264Feb 1, 2023Updated 3 years ago
- ☆115Oct 16, 2021Updated 4 years ago
- Boosting the training of physics informed neural networks with transfer learning☆27Jun 5, 2021Updated 5 years ago
- FrontISTR is an open-source parallel FEM software program. This software had been continuously developed and supported by the FrontISTR s…☆12Apr 8, 2024Updated 2 years ago
- Laminar flow prediction using graph neural networks☆32Jan 17, 2025Updated last year
- ☆65Mar 22, 2023Updated 3 years ago
- Physics-informed neural networks with hard constraints for inverse design☆160Nov 21, 2021Updated 4 years ago
- Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks☆12Jul 29, 2023Updated 2 years ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Subset simulation is a method of estimating low probability events. Here I adapt SS to perform well with correlated inputs.☆11Jan 9, 2019Updated 7 years ago
- Dynamic weight strategy of physics-informed neural networks for the 2D Navier-Stokes equations☆14Sep 1, 2022Updated 3 years ago
- POD-PINN code and manuscript☆60Nov 10, 2024Updated last year
- Official code for "DMIS: Dynamic Mesh-based Importance Sampling for Training Physics-Informed Neural Networks" (AAAI 2023)☆18Jan 17, 2024Updated 2 years ago
- Simplified implementation of locally adaptive activation functions (LAAF) with slope recovery for deep and physics-informed neural networ…☆31Mar 8, 2021Updated 5 years ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆26Apr 25, 2024Updated 2 years ago
- Must-read Papers on Physics-Informed Neural Networks.☆1,504Dec 8, 2023Updated 2 years ago
- Implementation of the SoftAdapt paper (techniques for adaptive loss balancing of multi-tasking neural networks)☆33Mar 16, 2024Updated 2 years ago
- Numerical assessments of a nonintrusive surrogate model based on recurrent neural networks and proper orthogonal decomposition: Rayleigh …☆10Dec 2, 2022Updated 3 years ago
- Proton VPN Special Offer - Get 70% off • AdSpecial partner offer. Trusted by over 100 million users worldwide. Tested, Approved and Recommended by Experts.
- We propose a conservative physics-informed neural network (cPINN) on decompose domains for nonlinear conservation laws. The conservation …☆80Feb 1, 2023Updated 3 years ago
- This repository offers a collection of simulation datasets from mechanical simulations of metamaterials. Jupyter notbooks demonstrate how…☆17Nov 1, 2022Updated 3 years ago
- Deep Learning for Structural Health monitoring☆22Sep 27, 2024Updated last year
- MTAdam: Automatic Balancing of Multiple Training Loss Terms☆37Nov 21, 2020Updated 5 years ago
- Physics-informed neural networks for highly compressible flows 🧠🌊☆30Nov 26, 2023Updated 2 years ago
- Demo code for PPINN paper: https://www.sciencedirect.com/science/article/pii/S0045782520304357☆11Oct 23, 2020Updated 5 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆43Jun 24, 2022Updated 3 years ago
- DAS: A deep adaptive sampling method for solving high-dimensional partial differential equations☆40Nov 20, 2024Updated last year
- A-PINN: Auxiliary physics informed neural networks for forward and inverse problems of nonlinear integro-differential equations☆24Sep 20, 2022Updated 3 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- Official Github Repository for paper "Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (…☆13Jun 10, 2023Updated 3 years ago
- ☆41May 8, 2020Updated 6 years ago
- ☆432Nov 14, 2025Updated 7 months ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆297Oct 12, 2021Updated 4 years ago
- Sequential Monte Carlo Method for Reliability Estimation of Complex Civil Engineering Structures☆17Jan 7, 2021Updated 5 years ago
- ☆175Jun 27, 2022Updated 3 years ago
- ☆217Feb 16, 2024Updated 2 years ago