Bayesian optimized physics-informed neural network for parameter estimation
☆33Nov 20, 2024Updated last year
Alternatives and similar repositories for BOPINN
Users that are interested in BOPINN are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Bayesian Physics-Informed Neural Networks for Robust System Identification of Power Systems☆14May 17, 2023Updated 3 years ago
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆18Apr 12, 2025Updated last year
- Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (ICLR 2024)☆26Jun 7, 2024Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆79Sep 13, 2021Updated 4 years ago
- Physics_Informed Bayesian Optimization☆16Nov 13, 2023Updated 2 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Physics Informed Neural Networks (PINNs) is a machine learning technique that incorporates physical laws and constraints into the neural …☆12Sep 27, 2024Updated last year
- ☆12Jun 22, 2025Updated last year
- Nonnegative Tensor Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning☆11Aug 23, 2026Updated last week
- B-PINN - Jax - HMC tutorial☆22Mar 31, 2023Updated 3 years ago
- Tensoflow 2 implementation of physics informed deep learning.☆27Sep 12, 2020Updated 5 years ago
- ☆11Feb 8, 2023Updated 3 years ago
- Research/development of physics-informed neural networks for dynamic systems☆33Nov 25, 2024Updated last year
- A software package for flexible HPC GPs☆16Aug 11, 2026Updated 2 weeks ago
- Physics-Informed Neural Networks Trained with Particle Swarm Optimization☆29Sep 20, 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.
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆16May 27, 2024Updated 2 years ago
- Implementation of Physics-Informed PointNet (PIPN) for weakly-supervised learning of 2D linear elasticity (plane stress) on multiple sets…☆13Apr 11, 2024Updated 2 years ago
- [ICML 2024] Official Pytorch implementation of the paper "A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions…☆22Nov 15, 2025Updated 9 months ago
- Modern Gaussian Processes: Scalable Inference and Novel Applications☆20Jul 13, 2019Updated 7 years ago
- This is the official implementation of physics-informed neural networks for functional differential equations (Functional PINN) proposed …☆12Apr 9, 2025Updated last year
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆22Mar 25, 2023Updated 3 years ago
- Physics-Informed Neural Network, Finite Element Method enhanced neural network, and FEM data-based neural network☆20May 8, 2026Updated 3 months ago
- Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…☆15Apr 12, 2024Updated 2 years ago
- Implementation of Dabrowski et. al., "Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wi…☆24Apr 2, 2024Updated 2 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆90Jul 15, 2022Updated 4 years ago
- xAct tutorials presented at Guangzhou University☆18Sep 16, 2019Updated 6 years ago
- Identification of Bouc–Wen type models using the transitional Markov chain Monte Carlo method☆15Mar 10, 2025Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆20Dec 8, 2023Updated 2 years ago
- Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs + Adaptative Loss Weights with JAX 📓 Check out our various notebooks to g…☆51Aug 14, 2026Updated 2 weeks ago
- Prior Sampling for high dimension data with domain knowledge.☆10Jan 11, 2022Updated 4 years ago
- Code for the paper "The Random Feature Model for Input-Output Maps between Banach Spaces" (SIREV SIGEST 2024, SISC 2021)☆15Aug 8, 2024Updated 2 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆43Jul 17, 2025Updated last year
- implementation of physics-informed variational auto-encoder☆20Oct 26, 2023Updated 2 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.
- A matlab toolkit for meshfree approximation schemes☆12Aug 4, 2020Updated 6 years ago
- Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction☆30Feb 27, 2026Updated 6 months ago
- Data-guided physics-informed neural networks☆18Jul 16, 2024Updated 2 years ago
- Python Library for Generalized Gaussian Process Modeling☆28Aug 12, 2026Updated 2 weeks ago
- ☆11Oct 15, 2025Updated 10 months ago
- Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control☆58May 16, 2022Updated 4 years ago
- Physics Informed Neural Network (PINN) for Burgers' equation.☆76Aug 21, 2024Updated 2 years ago