Crunch-UQ4MI / neuraluq
☆167Updated last year
Alternatives and similar repositories for neuraluq:
Users that are interested in neuraluq are comparing it to the libraries listed below
- Characterizing possible failure modes in physics-informed neural networks.☆128Updated 3 years ago
- ☆192Updated 3 years ago
- PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.☆98Updated 9 months ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆63Updated 2 years ago
- ☆116Updated 5 years ago
- ☆156Updated last year
- Physics-informed learning of governing equations from scarce data☆134Updated last year
- ETH Zürich Deep Learning in Scientific Computing Master's course 2023☆106Updated 7 months ago
- ☆130Updated 2 years ago
- ☆89Updated 3 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆145Updated 5 years ago
- Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…☆146Updated last month
- ☆62Updated 5 years ago
- hPINN: Physics-informed neural networks with hard constraints☆125Updated 3 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆333Updated last year
- Basic implementation of physics-informed neural networks for solving differential equations☆81Updated 2 months ago
- Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonli…☆178Updated 2 years ago
- ☆268Updated last week
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆67Updated last year
- ☆320Updated 2 years ago
- This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means…☆176Updated 4 years ago
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆114Updated 3 years ago
- Hidden physics models: Machine learning of nonlinear partial differential equations☆143Updated 5 years ago
- Applications of PINOs☆118Updated 2 years ago
- Code for the paper "Poseidon: Efficient Foundation Models for PDEs"☆131Updated 3 months ago
- ☆113Updated 4 months ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆152Updated 4 months ago
- Implementing a physics-informed DeepONet from scratch☆34Updated last year
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆47Updated 4 years ago
- Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism" [AAAI-MLPS 2021]☆208Updated 3 years ago