64 skills found · Page 1 of 3
lululxvi / DeepxdeA library for scientific machine learning and physics-informed learning
lululxvi / DeeponetLearning nonlinear operators via DeepONet based on the universal approximation theorem of operators
jdtoscano94 / NABLA SciMLPhysics Informed Machine Learning Tutorials (Pytorch and Jax)
PredictiveIntelligenceLab / Physics Informed DeepONetsNo description available
lu-group / Deeponet FnoA comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
SciML / FluxNeuralOperators.jlDeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
katiana22 / Latent DeeponetSource code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
katiana22 / TL DeepONetSource code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
ShuaiGuo16 / PI DeepONetImplementing a physics-informed DeepONet from scratch
PredictiveIntelligenceLab / Long Time Integration PI DeepONetsNo description available
SciML / OperatorLearning.jlNo need to train, he's a smooth operator
dtu-act / Deeponet Acoustic Wave PropCode for training and inferring acoustic wave propagation in 3D
lu-group / Multifidelity DeeponetMultifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport
HewlettPackard / Separable Operator NetworksOfficial repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
lu-group / Fourier Deeponet FwiFourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
SciML / NeuralOperators.jlDeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
ehsanhaghighat / En DeepONetRepository for sharing code and data assocaited with En-DeepONet architecture
pankajkmishra / NodeLabNodeLab is a simple MATLAB-repository for node-generation and adaptive refinement for testing, and implementing various meshfree methods (including physics-informed neural networks, PINNs and DeepOnet) for solving PDEs in arbitrary domains.
jangseop-park / Point DeepONetNo description available
rfarell / Reduced Order Modeling TutorialsA collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Easily runnable on Google Colab.
