PredictiveIntelligenceLab / USNCCM15-Short-Course-Recent-Advances-in-Physics-Informed-Deep-LearningView on GitHub
☆118Jul 28, 2019Updated 6 years ago
Alternatives and similar repositories for USNCCM15-Short-Course-Recent-Advances-in-Physics-Informed-Deep-Learning
Users that are interested in USNCCM15-Short-Course-Recent-Advances-in-Physics-Informed-Deep-Learning are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- ☆64Mar 22, 2023Updated 3 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆21Mar 25, 2023Updated 3 years ago
- Deep learning for Engineers - Physics Informed Deep Learning☆366Dec 20, 2023Updated 2 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆50Jul 23, 2020Updated 5 years ago
- ☆261Oct 14, 2021Updated 4 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- XPINN code written in TensorFlow 2☆28Feb 1, 2023Updated 3 years ago
- An implementation of a neural network training routine using derivative information in Pytorch.☆11Dec 19, 2020Updated 5 years ago
- TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).☆267Nov 30, 2023Updated 2 years ago
- ☆21Sep 28, 2020Updated 5 years ago
- Lecture and hands-on material for Track 8- Machine Learning of Argonne Training Program on Extreme-Scale Computing☆45Sep 5, 2025Updated 8 months ago
- A place to share problems solved with SciANN☆309Nov 6, 2023Updated 2 years ago
- ☆63Jul 24, 2019Updated 6 years ago
- Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations☆5,872Feb 11, 2026Updated 3 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆40Jul 12, 2023Updated 2 years ago
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- ☆15Oct 25, 2021Updated 4 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
- 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
- Physics-informed neural networks☆16Nov 26, 2020Updated 5 years ago
- Benchmark for learning stiff problems using physics-informed machine learning☆13Dec 15, 2021Updated 4 years ago
- ☆20May 29, 2020Updated 5 years ago
- Automatic Differentiation Library for Computational and Mathematical Engineering☆322Oct 18, 2023Updated 2 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆98Aug 17, 2023Updated 2 years ago
- POD-PINN code and manuscript☆59Nov 10, 2024Updated last year
- Deploy open-source AI quickly and easily - Special Bonus Offer • AdRunpod Hub is built for open source. One-click deployment and autoscaling endpoints without provisioning your own infrastructure.
- Code to estimate Renormalized Mutual Information in simple settings☆13Mar 8, 2021Updated 5 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆34Oct 30, 2023Updated 2 years ago
- ☆20Apr 26, 2024Updated 2 years ago
- Data-driven Identification of 2D Partial Differential Equations using Extracted Physical Features☆12Apr 23, 2021Updated 5 years ago
- ☆11Apr 12, 2019Updated 7 years ago
- pyPCGA: fast and scalable inverse modeling approach☆27Mar 18, 2026Updated 2 months ago
- Physics-Informed Neural Networks for solving PDEs (bachelor project)☆10Mar 20, 2023Updated 3 years ago
- ☆34Oct 5, 2020Updated 5 years ago
- A library for scientific machine learning and physics-informed learning☆4,177Mar 1, 2026Updated 2 months ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations☆290Jul 30, 2022Updated 3 years ago
- ME 539 - Introduction to Scientific Machine Learning☆127Feb 22, 2026Updated 3 months ago
- CME250Q: Introduction to quantum computing and quantum algorithms☆15Nov 5, 2019Updated 6 years ago
- Convolutional Solvers for Partial Differential Equations☆28Jun 29, 2020Updated 5 years ago
- Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs☆95May 11, 2022Updated 4 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆62Dec 7, 2020Updated 5 years ago
- Volterra Integral Equation Solver☆12Feb 3, 2016Updated 10 years ago