☆201Apr 3, 2025Updated 11 months ago
Alternatives and similar repositories for neuraluq
Users that are interested in neuraluq are comparing it to the libraries listed below
Sorting:
- ☆13Dec 5, 2022Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆78Aug 4, 2023Updated 2 years ago
- ☆10Jul 16, 2021Updated 4 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆21Jun 20, 2024Updated last year
- ☆41Sep 11, 2023Updated 2 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Jun 4, 2023Updated 2 years ago
- ☆10Mar 18, 2023Updated 2 years ago
- ☆35Jan 5, 2024Updated 2 years ago
- ☆15Mar 3, 2023Updated 3 years ago
- ☆244Oct 14, 2021Updated 4 years ago
- A library for scientific machine learning and physics-informed learning☆3,907Mar 1, 2026Updated last week
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Jul 12, 2023Updated 2 years ago
- Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data☆151Oct 18, 2019Updated 6 years ago
- ☆15Oct 25, 2021Updated 4 years ago
- PDEBench: An Extensive Benchmark for Scientific Machine Learning☆1,078Feb 24, 2026Updated last week
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago
- Repository for sharing code and data assocaited with En-DeepONet architecture☆35Jan 15, 2024Updated 2 years ago
- A Python module that implements tools for the simulation and identification of random fields using the Karhunen-Loeve expansion represent…☆24Jun 21, 2016Updated 9 years ago
- ☆55Oct 9, 2022Updated 3 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆88Aug 26, 2025Updated 6 months ago
- A novel DeepONet architecture that is specifically designed for generating predictions on different 3D geometries discretized by differen…☆24Jul 25, 2024Updated last year
- An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic di…☆31Oct 25, 2022Updated 3 years ago
- A place to share problems solved with SciANN☆305Nov 6, 2023Updated 2 years ago
- ☆33Aug 31, 2022Updated 3 years ago
- This repository contains code, which was used to generate large-scale results in the HINTS paper.☆36Oct 17, 2024Updated last year
- Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…☆118Mar 1, 2022Updated 4 years ago
- ☆36Sep 3, 2021Updated 4 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆362Dec 20, 2023Updated 2 years ago
- ☆207Feb 16, 2024Updated 2 years ago
- Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors☆14Apr 12, 2025Updated 10 months ago
- Original implementation of fast PINN optimization with RBA weights☆70Sep 11, 2025Updated 5 months ago
- Domain Agnostic Fourier Neural Operators (DAFNO)☆19Sep 3, 2024Updated last year
- Deep Learning - Predicting using Neural Ordinary Differential Equations - torchdiffeq.☆15Nov 18, 2020Updated 5 years ago
- Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…☆16Sep 18, 2023Updated 2 years ago
- Physics-informed learning of governing equations from scarce data☆167Jul 19, 2023Updated 2 years ago
- Multi-fidelity Gaussian Process☆29Jan 10, 2021Updated 5 years ago
- ☆46Jun 10, 2025Updated 8 months ago
- ☆24Mar 3, 2023Updated 3 years ago
- Multi-fidelity classification with Gaussian process☆18Jul 18, 2023Updated 2 years ago